Topic Editors

Prof. Dr. Kuo-Ping Lin
Department of Industrial Engineering and Enterprise Information, Tunghai University, Taichung 40704, Taiwan
Prof. Dr. Chien-Chih Wang
Department of Industrial Engineering and Management, Ming Chi University of Technology, New Taipei City 24301, Taiwan
Dr. Chieh-Liang Wu
1. Department of Computer Science, Tunghai University, Taichung 407224, Taiwan
2. Department of Critical Care Medicine, Taichung Veterans General Hospital, Taichung 40704, Taiwan
3. Department of Automatic Control Engineering, Feng Chia University, Taichung, Taiwan
Dr. Liang Dong
Department of Public Policy, School of Energy and Environment, City University of Hong Kong, Hong Kong SAR 999077, China

Multi-Criteria Decision Making

Abstract submission deadline
closed (30 September 2022)
Manuscript submission deadline
30 December 2022
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21415

Topic Information

Dear Colleagues,

Multi-criteria decision-making (MCDM) needs to consider multiple functions/attributes/criteria/objectives and conflicts with the real world at the same time in management decision-making. MCDM provides a practical problem-solving structure, selects appropriate scientific methods, and assists decision-makers in correctly making judgements in various decision problems. Therefore, the problem types of multi-criteria decision-making generally come from common phenomena in the real world. Multi-criteria decision-making problems can be roughly divided into two categories: planning/design/optimization problems and evaluation/selection/improvement problems (multi-attribute decision-making MADM). The problem types include evaluation problems, planning/design problems, ranking selection problems, and improvement problems. Many industries have been using the MCDM method to solve actual problems, such as those from medicine, supply chain, industrial ecology, energy, manufacturing, engineering, and various industries. Extrapolative analysis and methodology include an analytic hierarchy process, data envelopment analysis, ELECTRE, PROMETHEE, techniques for order preference by similarity to ideal solution, etc. Furthermore, big data/ Machine Learning/Artificial Intelligence have also been successfully applied in MCDM models, and the MCDM method can effectively make decisions in Industry 4.0. We are looking for new research based on the novel MCDM method for solving actual problems.

Prof. Dr. Kuo-Ping Lin
Prof. Dr. Chien-Chih Wang
Dr. Chieh-Liang Wu
Dr. Liang Dong
Topic Editors

Keywords

  • multi-criteria decision-making
  • medicine
  • industrial ecology
  • engineering
  • Industry 4.0

Participating Journals

Journal Name Impact Factor CiteScore Launched Year First Decision (median) APC
Applied Sciences
applsci
2.838 3.7 2011 17.4 Days 2300 CHF Submit
Mathematics
mathematics
2.592 2.9 2013 17.8 Days 1800 CHF Submit
Symmetry
symmetry
2.940 4.3 2009 13.8 Days 1800 CHF Submit
International Journal of Environmental Research and Public Health
ijerph
4.614 4.5 2004 22.5 Days 2500 CHF Submit
Forecasting
forecasting
- - 2019 15.3 Days 1400 CHF Submit

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Published Papers (32 papers)

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Article
Spatial Predictive Modeling of the Burning of Sugarcane Plots in Northeast Thailand with Selection of Factor Sets Using a GWR Model and Machine Learning Based on an ANN-CA
Symmetry 2022, 14(10), 1989; https://doi.org/10.3390/sym14101989 - 23 Sep 2022
Abstract
The main purpose of the study is to apply symmetry principles to general mathematical modelling based on multi-criteria decision making (MCDM) approach for use in development in conjunction with geographic weighted regression (GWR) model and optimize the artificial neural network-cellular automaton (ANN-CA) model [...] Read more.
The main purpose of the study is to apply symmetry principles to general mathematical modelling based on multi-criteria decision making (MCDM) approach for use in development in conjunction with geographic weighted regression (GWR) model and optimize the artificial neural network-cellular automaton (ANN-CA) model for forecasting the sugarcane plot burning area of Northeast Thailand. First, to calculate the service area boundaries of sugarcane transport that caused the burning of sugarcane with a fire radiative power (FRP) values using spatial correlation analysis approach. Second, the analysis of the spatial factors influencing sugarcane burning. The study uses the approach of symmetry in the design of algorithm for finding the optimal service boundary distance (called as cut-off) in the analysis of hot-spot clustering and uses calculations with the geographic information system (GIS) approach, and the final stage is the use of screened independent variable factors to predict the plots of burned sugarcane in 2031. The results showed that the positively related factors for the percentage of cane plot sintering in the sub-area units of each sugar plant's service were the distance to transport sugarcane plots index and percentage of sugarcane plantations in service areas, while the negative coefficients were FRP differences and density of sugarcane yield factors, according to the analysis with a total of seven spatial variables. The best GWR models display local R2 values at levels of 0.902 to 0.961 in the service zones of Khonburi and Saikaw. An influential set of independent variables can increase the accuracy of the ANN-CA model in forecasting with kappa statistical estimates in the range of 0.81 to 0.85 The results of the study can be applied to other regions of Thailand, including countries with similar sugarcane harvesting industries, to formulate policies to reduce the exposure of sugarcane harvested by burning methods and to support the transportation of sugarcane within the appropriate scope of service so that particulate matter less than 2.5 microns () can be reduced. Full article
(This article belongs to the Topic Multi-Criteria Decision Making)
Article
Selecting Optimal Cultural Tourism for Indigenous Tribes by Fuzzy MCDM
Mathematics 2022, 10(17), 3121; https://doi.org/10.3390/math10173121 - 31 Aug 2022
Abstract
Unique Indigenous cultures have become increasingly attractive and prevalent in the tourism market. More and more Indigenous tribes wish to improve their economic situation by developing a tourism industry with ethnic culture as the core attraction. The main arguments regarding Indigenous tourism involve [...] Read more.
Unique Indigenous cultures have become increasingly attractive and prevalent in the tourism market. More and more Indigenous tribes wish to improve their economic situation by developing a tourism industry with ethnic culture as the core attraction. The main arguments regarding Indigenous tourism involve cultural vicissitudes between the past and present, indicating that appropriate tourism development and cultural conservation should be carried out. As cultural features are characterized by symbols, complexity, shareability, and diversity, it is challenging to measure the aspects of cultural vicissitudes. This study adopted a mixed multiple-criteria decision-making (MCDM) model, in which the fuzzy analytic hierarchy process (FAHP) and fuzzy technique for order preference by similarity to ideal solution (FTOPSIS) were established to assist Indigenous tribes in selecting an optimal cultural tourism mode. Based on a literature review, a hierarchical structure for cultural vicissitude criteria selection is constructed. FAHP was applied to determine the importance and weights of criteria. Among the considered criteria, material culture, institutional culture, and spiritual culture with the values of 0.5478, 0.2791, and 0.1731 were determined as the most effective criteria for developing Indigenous tourism rankings, respectively. The optimal cultural tourism model ranking was obtained using the FTOPSIS approach. Full article
(This article belongs to the Topic Multi-Criteria Decision Making)
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Article
Exploring a Dualism of Human Rationality: Experimental Study of a Cheating Contest Game
Int. J. Environ. Res. Public Health 2022, 19(13), 7675; https://doi.org/10.3390/ijerph19137675 - 23 Jun 2022
Abstract
Rational behavior is a standard assumption in science. Indeed, rationality is required for environmental action towards net-zero emissions or public health interventions during the SARS-CoV-2 pandemic. Yet, little is known about the elements of rationality. This paper explores a dualism of rationality comprised [...] Read more.
Rational behavior is a standard assumption in science. Indeed, rationality is required for environmental action towards net-zero emissions or public health interventions during the SARS-CoV-2 pandemic. Yet, little is known about the elements of rationality. This paper explores a dualism of rationality comprised of optimality and consistency. By designing a new guessing game, we experimentally uncover and disentangle two building blocks of human rationality: the notions of optimality and consistency. We find evidence that rationality is largely associated to optimality and weakly to consistency. Remarkably, under uncertainty, rationality gradually shifts to a heuristic notion. Our findings provide insights to better understand human decision making. Full article
(This article belongs to the Topic Multi-Criteria Decision Making)
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Article
Hybrid LSTM-ARMA Demand-Forecasting Model Based on Error Compensation for Integrated Circuit Tray Manufacturing
Mathematics 2022, 10(13), 2158; https://doi.org/10.3390/math10132158 - 21 Jun 2022
Cited by 1
Abstract
Demand forecasting plays a crucial role in a company’s operating costs. Excessive inventory can increase costs and unnecessary waste can be reduced if managers plan for uncertain future demand and determine the most favorable decisions. Managers are demanding increasing accuracy in forecasting as [...] Read more.
Demand forecasting plays a crucial role in a company’s operating costs. Excessive inventory can increase costs and unnecessary waste can be reduced if managers plan for uncertain future demand and determine the most favorable decisions. Managers are demanding increasing accuracy in forecasting as technology advances. Most of the literature discusses forecasting results’ inaccuracy by suspending the model and reloading the data for model retraining and correction, which is extensively employed but causes a bottleneck in practice since users do not have the sufficient ability to correct the model. This study proposes an error compensation mechanism and uses the individuals and moving-range (I-MR) control chart to evaluate the requirement for compensation to solve the current bottleneck using forecasting models. The approach is validated using the case companies’ historical data, and the model is developed using a rolling long short-term memory (LSTM) to output the predicted values; then, five indicators are proposed for screening to determine the prediction statistics to be subsequently employed. Root mean squared error (RMSE), mean absolute percentage error (MAPE), and mean absolute error (MAE) compare the LSTM, rolling LSTM combined index, and LSTM-autoregressive moving average (ARMA) models. The results demonstrate that the RMSE, MAPE, and MAE of LSTM-ARMA are smaller than those of the other two models, indicating that the error compensation mechanism that is proposed in this study can enhance the prediction’s accuracy. Full article
(This article belongs to the Topic Multi-Criteria Decision Making)
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Article
Multiple Scenarios of Quality of Life Index Using Fuzzy Linguistic Quantifiers: The Case of 85 Countries in Numbeo
Mathematics 2022, 10(12), 2091; https://doi.org/10.3390/math10122091 - 16 Jun 2022
Abstract
In economic development, in addition to comparing the gross domestic product (GDP) between nations, it is critical to assess the quality of life to gain a holistic perspective of their different aspects. However, the quality of life index (QOLI) is a subjective term [...] Read more.
In economic development, in addition to comparing the gross domestic product (GDP) between nations, it is critical to assess the quality of life to gain a holistic perspective of their different aspects. However, the quality of life index (QOLI) is a subjective term that can be difficult to quantify. Although this composite index is typically calculated using universal weights proposed by experts to aggregate indicators, such as safety indexes, healthcare indexes, pollution indexes, and housing indicators, it is complicated to balance multiple dimensions whose weights are adjusted to account for different countries’ circumstances. Therefore, this paper aims to construct various scenarios of the QOLI, using linguistic quantifiers of the ordered weighted averaging (OWA) operator, and the 2-tuple linguistic model. Numbeo, one of the largest quality of life information databases, was used in this paper to estimate the QOLI in 85 countries. Uncertainty and sensitivity analyses were employed to assess the robustness of the QOLI. The results of the proposed model are compared with those obtained using the Numbeo formulation. The results show that the proposed model increases the linguistic interpretability of the QOLI, and obtains different QOLIs, based on diverse country contexts. Full article
(This article belongs to the Topic Multi-Criteria Decision Making)
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Article
Performance Evaluation of Enterprise Collaboration Based on an Improved Elman Neural Network and AHP-EW
Appl. Sci. 2022, 12(12), 5941; https://doi.org/10.3390/app12125941 - 10 Jun 2022
Abstract
In order to mitigate the influence of human subjectivity on indicator weights in the performance evaluation of enterprise collaboration, and explore the nonlinear relationship between the enterprise collaboration influencing factors and the evaluation results, this paper propose a combined performance evaluation model based [...] Read more.
In order to mitigate the influence of human subjectivity on indicator weights in the performance evaluation of enterprise collaboration, and explore the nonlinear relationship between the enterprise collaboration influencing factors and the evaluation results, this paper propose a combined performance evaluation model based on AHP-EW and an improved Elman neural network. Firstly, based on the characteristics of collaboration among manufacturing enterprises, the evaluation system for the collaborative performance of manufacturing enterprises is constructed from three dimensions. Moreover, this study combines subjective and objective weighting methods to obtain comprehensive weights that take into account both expert experience and objective information. Then, an improved Elman neural network is proposed and trained to predict and evaluate the collaborative performance indicator data, which greatly shortens the evaluation time and improves evaluation accuracy. The experimental results show that the proposed model has a faster convergence speed and higher accuracy, which will provide a valuable reference for decision making and the management of enterprise collaboration. Full article
(This article belongs to the Topic Multi-Criteria Decision Making)
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Article
Hesitant Fuzzy Variable and Distribution
Symmetry 2022, 14(6), 1184; https://doi.org/10.3390/sym14061184 - 08 Jun 2022
Abstract
In recent decades, the hesitant fuzzy set theory has been used as a main tool to describe the hesitant fuzzy phenomenon, which usually exists in multiple attributes of decision making. However, in the general case concerning numerous decision-making problems, values of attributes are [...] Read more.
In recent decades, the hesitant fuzzy set theory has been used as a main tool to describe the hesitant fuzzy phenomenon, which usually exists in multiple attributes of decision making. However, in the general case concerning numerous decision-making problems, values of attributes are real numbers, and some decision makers are hesitant about these values. Consequently, the possibility of taking a number contains several possible values in the real number interval [0, 1]. As a result, the hesitant possibility of hesitant fuzzy events cannot be inferred from the given hesitant fuzzy set which only presents the hesitant membership degree with respect to an element belonging to this one. To address this problem, this paper explores the axiomatic system of the hesitant possibility measure from which the hesitant fuzzy theory is constructed. Firstly, a hesitant possibility measure from the pattern space to the power set of [0, 1] is defined, and some properties of this measure are discussed. Secondly, a hesitant fuzzy variable, which is a symmetric set-valued function on the hesitant possibility measure space, is proposed, and the distribution of this variable and one of its functions are studied. Finally, two examples are shown in order to explain the practical applications of the hesitant fuzzy variable in the hesitant fuzzy graph model and decision-making considering hesitant fuzzy attributes. The relevant research results of this paper provide an important mathematical tool for hesitant fuzzy information processing from another new angle different from the theory of hesitant fuzzy sets, and can be utilized to solve decision problems in light of the hesitant fuzzy value of multiple attributes. Full article
(This article belongs to the Topic Multi-Criteria Decision Making)
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Article
Smartphone Market Analysis with Respect to Brand Performance Using Hybrid Multicriteria Decision Making Methods
Mathematics 2022, 10(11), 1861; https://doi.org/10.3390/math10111861 - 29 May 2022
Cited by 1
Abstract
In this era of information explosion, smartphones have become a necessary device in our daily life. In order to select a better smartphone, most users try to collect more attributes to help them purchase their own smartphones, including the brand image from the [...] Read more.
In this era of information explosion, smartphones have become a necessary device in our daily life. In order to select a better smartphone, most users try to collect more attributes to help them purchase their own smartphones, including the brand image from the advertisements, features from the specifications, word-of-mouth from their peers, and the average sales from some secondary data webs. In order to assist the users to evaluate the brand performance from the market attributes, in this paper, we selected nine smartphone brands and used multi-criteria decision-making methods to rank the smartphones’ functions. We first use TOPSIS to evaluate word-of-mouth, together with average sales collected from the website of each brand, and the brand image obtained by the use of questionnaires. Finally, we summarize the final rankings of these smartphone brands. The brand performance analysis shows that our proposed hybrid method can significantly derive the overall rankings of smartphone brands. Full article
(This article belongs to the Topic Multi-Criteria Decision Making)
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Review
Application of Multi-Criteria Decision-Making Analysis to Rural Spatial Sustainability Evaluation: A Systematic Review
Int. J. Environ. Res. Public Health 2022, 19(11), 6572; https://doi.org/10.3390/ijerph19116572 - 27 May 2022
Cited by 2
Abstract
The rational allocation of spatial resources is an important factor to ensure the sustainable development of rural areas, and effective pre-emptive spatial evaluation is the prerequisite for identifying the predicament of rural resource allocation. Multi-criteria decision-making analysis has advantages in solving multi-attribute and [...] Read more.
The rational allocation of spatial resources is an important factor to ensure the sustainable development of rural areas, and effective pre-emptive spatial evaluation is the prerequisite for identifying the predicament of rural resource allocation. Multi-criteria decision-making analysis has advantages in solving multi-attribute and multi-objective decision-making problems, and has been used in sustainability evaluation research in various disciplines in recent years. Previous studies have proved the value of spatial evaluation using multi-criteria decision analysis in guiding rural incremental development and inventory updates, but systematic reviews of the previous literature from a multidisciplinary perspective and studies of the implementation steps of the evaluation framework are lacking. In the current paper, the research is reviewed from the two levels of quantitative statistics and research content, and through vertical and horizontal comparisons based on three common operating procedures: standard formulation, weight distribution, and ranking and verification. Through the results, the application status and characteristics of the MCDA method in related research are determined, and five research foci in the future are proposed. Full article
(This article belongs to the Topic Multi-Criteria Decision Making)
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Article
Cultural Adaptation and Validity Testing of the Portuguese Version of the Health Literacy Questionnaire (HLQ)
Int. J. Environ. Res. Public Health 2022, 19(11), 6465; https://doi.org/10.3390/ijerph19116465 - 26 May 2022
Cited by 1
Abstract
Background: Health literacy is considered a determinant of self-management behaviors and health outcomes among people with diabetes. The assessment of health literacy is central to understanding the health needs of a population. This study aimed to adapt the Health Literacy Questionnaire (HLQ) to [...] Read more.
Background: Health literacy is considered a determinant of self-management behaviors and health outcomes among people with diabetes. The assessment of health literacy is central to understanding the health needs of a population. This study aimed to adapt the Health Literacy Questionnaire (HLQ) to the Portuguese context and to examine the psychometric properties of a population of people with diabetes. Methods: Data were collected using a self-administrated questionnaire from 453 people with diabetes in a specialized diabetes care unit. Analysis included item difficulty level, composite scale reliability, and confirmatory factor analysis (CFA). Results: The HLQ showed that the items were easily understood by participants. Composite reliability ranged from 0.74 to 0.83. A nine-factor CFA model was fitted to the 44 items. Given the very restricted model, the fit was quite satisfactory [χ2wlsmv = 2147.3 (df = 866), p = 0.001; CFI = 0.931, TLI = 0.925, RMSEA = 0.057 (90% C.I. 0.054–0.060), and WRMR = 1.528]. Conclusion: The Portuguese version of the HLQ has shown satisfactory psychometric properties across its nine separate scales in people with diabetes. Given the strong observed properties of the HLQ across cultures, languages, and diseases, the HLQ is likely to be a useful tool in a range of Portuguese settings. Full article
(This article belongs to the Topic Multi-Criteria Decision Making)
Article
Measuring the Attractiveness of Cities to Receive Investments in Regional Airport Infrastructure
Mathematics 2022, 10(10), 1734; https://doi.org/10.3390/math10101734 - 19 May 2022
Abstract
The vast Brazilian territory and the accelerated economic growth of the cities of the country’s interior in recent years have created a favourable environment for the expansion of regional aviation. In 2015, the Brazilian Government launched a program of investments in regional airports [...] Read more.
The vast Brazilian territory and the accelerated economic growth of the cities of the country’s interior in recent years have created a favourable environment for the expansion of regional aviation. In 2015, the Brazilian Government launched a program of investments in regional airports equipping them to receive commercial flights. However, the economic crisis and the scarcity of resources drive the prioritisation of projects with a greater economic and social return. This article aims to present a multicriteria decision aid (MCDA) model to measure cities’ attractiveness to receive investments in regional airports. The MCDA approach can deal with multiple indicators and different points of view and provide systematised steps for supporting decision-makers. For this purpose, we selected 12 criteria among the evaluation parameters identified in the literature, which led to the construction of the evaluation model and elaborating the ranking of the localities participating in the investment program. This study can contribute scientifically by proposing the use of an MCDA approach to support decisions related to logistics and infrastructure. It can help managers and practitioners provide a structured and systematised model to address decisions related to airport investments. Full article
(This article belongs to the Topic Multi-Criteria Decision Making)
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Article
Selection of Production Reliability Indicators for Project Simulation Model
Appl. Sci. 2022, 12(10), 5012; https://doi.org/10.3390/app12105012 - 16 May 2022
Abstract
Due to technological enhancements, traditional, qualitative decision-making methods are usually replaced by data-driven decision-making even in smaller companies. Process simulation is one of these solutions, which can help companies avoid costly failures as well as evaluate positive or negative effects. The reason for [...] Read more.
Due to technological enhancements, traditional, qualitative decision-making methods are usually replaced by data-driven decision-making even in smaller companies. Process simulation is one of these solutions, which can help companies avoid costly failures as well as evaluate positive or negative effects. The reason for this paper is twofold: first, authors conducted a Quality Function Deployment analysis to find the most vital reliability indicators in the field of production scheduling. The importance was acquired from the meta-analysis of papers published in major journals. The authors found 3 indicators to be the most important: mean time between failure (MTBF), mean repair time and mean downtime. The second part of the research is for the implementation of these indicators to the stochastic environment: possible means of application are proposed, confirming the finding with a case study in which 100 products must be produced. The database created from the simulation is analyzed in terms of major production KPIs, such as production quantity, total process time and efficiency of the production. The results of the study show that calculating with reliability issues in production during the negotiation of a production deadline supports business excellence. Full article
(This article belongs to the Topic Multi-Criteria Decision Making)
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Article
Influence of Initial Conditions on Wind Characteristics at a Bridge Middle Span in a U-Shaped Valley by CFD and AHP
Appl. Sci. 2022, 12(9), 4693; https://doi.org/10.3390/app12094693 - 06 May 2022
Abstract
The wind parameter distribution law at a bridge midspan in a U-shaped valley has important influence on the wind strength of this bridges. In this paper, the wind characteristics were researched by computational fluid dynamics (CFD). The surface roughness, the inlet wind speed, [...] Read more.
The wind parameter distribution law at a bridge midspan in a U-shaped valley has important influence on the wind strength of this bridges. In this paper, the wind characteristics were researched by computational fluid dynamics (CFD). The surface roughness, the inlet wind speed, the wind speed profile, and the oncoming wind direction were selected as the initial conditions; the wind speed, the wind attack angle, and the wind azimuth angle were set as wind parameters; and the effect of the four initial conditions on the wind parameters was comprehensively analyzed. An innovative quantification model used to connect the coefficient of sensitivity factors with scale values was established, and the influence of initial conditions on wind parameters was studied by analytic hierarchy process (AHP) for the first time. The results show that the spatial distribution of wind characteristics in a U-shaped valley is complex and obviously affected by the initial conditions. The established quantification model has certain practicability. The AHP evaluation results showed that the influence of the oncoming wind direction on wind parameters was the most obvious. The influence degree of oncoming wind direction and wind speed profile on wind speed was just as important, accounting for 77.4%. The sensitivity of wind attack angle to oncoming wind direction was 60.8%, which was much higher than the surface roughness, inlet wind speed, and wind speed profile. The influence degree of oncoming wind direction on wind azimuth angle was the sum of the other three initial conditions. Full article
(This article belongs to the Topic Multi-Criteria Decision Making)
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Article
Topological Data Analysis with Cubic Hesitant Fuzzy TOPSIS Approach
Symmetry 2022, 14(5), 865; https://doi.org/10.3390/sym14050865 - 22 Apr 2022
Cited by 1
Abstract
A hesitant fuzzy set (HFS) and a cubic set (CS) are two independent approaches to deal with hesitancy and vagueness simultaneously. An HFS assigns an essential hesitant grade to each object in the universe, whereas a CS deals with uncertain information in terms [...] Read more.
A hesitant fuzzy set (HFS) and a cubic set (CS) are two independent approaches to deal with hesitancy and vagueness simultaneously. An HFS assigns an essential hesitant grade to each object in the universe, whereas a CS deals with uncertain information in terms of fuzzy sets as well as interval-valued fuzzy sets. A cubic hesitant fuzzy set (CHFS) is a new computational intelligence approach that combines CS and HFS. The primary objective of this paper is to define topological structure of CHFSs under P(R)-order as well as to develop a new topological data analysis technique. For these objectives, we propose the concept of “cubic hesitant fuzzy topology (CHF topology)”, which is based on CHFSs with both P(R)-order. The idea of CHF points gives rise to the study of several properties of CHF topology, such as CHF closure, CHF exterior, CHF interior, CHF frontier, etc. We also define the notion of CHF subspace and CHF base in CHF topology and related results. We proposed two algorithms for extended cubic hesitant fuzzy TOPSIS and CHF topology method, respectively. The symmetry of optimal decision is analyzed by computations with both algorithms. A numerical analysis is illustrated to discuss similar medical diagnoses. We also discuss a case study of heart failure diagnosis based on CHF information and the modified TOPSIS approach. Full article
(This article belongs to the Topic Multi-Criteria Decision Making)
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Article
Multi-Criteria Decision Making in the PMEDM Process by Using MARCOS, TOPSIS, and MAIRCA Methods
Appl. Sci. 2022, 12(8), 3720; https://doi.org/10.3390/app12083720 - 07 Apr 2022
Cited by 3
Abstract
Multi-criteria decision making (MCDM) is used to determine the best alternative among various options. It is of great importance as it hugely affects the efficiency of activities in life, management, business, and engineering. This paper presents the results of a multi-criteria decision-making study [...] Read more.
Multi-criteria decision making (MCDM) is used to determine the best alternative among various options. It is of great importance as it hugely affects the efficiency of activities in life, management, business, and engineering. This paper presents the results of a multi-criteria decision-making study when using powder-mixed electrical discharge machining (PMEDM) of cylindrically shaped parts in 90CrSi tool steel. In this study, powder concentration, pulse duration, pulse off time, pulse current, and host voltage were selected as the input process parameters. Moreover, the Taguchi method was used for the experimental design. To simultaneously ensure minimum surface roughness (RS) and maximum material-removal speed (MRS) and to implement multi-criteria decision making, MARCOS (Measurement of Alternatives and Ranking according to Compromise Solution), TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution), and MAIRCA (Multi-Attributive Ideal–Real Comparative Analysis) methods were applied. Additionally, the weight calculation for the criteria was calculated using the MEREC (Method based on the Removal Effects of Criteria) method. From the results, the best alternative for the multi-criteria problem with PMEDM cylindrically shaped parts was proposed. Full article
(This article belongs to the Topic Multi-Criteria Decision Making)
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Article
Optimization of Urban Shelter Locations Using Bi-Level Multi-Objective Location-Allocation Model
by and
Int. J. Environ. Res. Public Health 2022, 19(7), 4401; https://doi.org/10.3390/ijerph19074401 - 06 Apr 2022
Cited by 5
Abstract
Recently, global natural disasters have occurred frequently and caused serious damage. As an important urban space resource and public service facility, the reasonable planning and layout optimization of shelters is very important to reduce the disaster loss and improve the sustainable development of [...] Read more.
Recently, global natural disasters have occurred frequently and caused serious damage. As an important urban space resource and public service facility, the reasonable planning and layout optimization of shelters is very important to reduce the disaster loss and improve the sustainable development of cities. Based on the review of location theory and models for shelter site selection, this study constructs a bi-level multi-objective location-allocation model, an accessibility, economy, and efficiency (AEE) model, based on sequential decision logic to maximize the economic sustainability and social utility. The model comprehensively considers factors such as the level of decision-making, the utilization efficiency, and capacity constraints of shelters. The gravity model is introduced to simulate the decision-making behavior of evacuees. A calculation example and its solution prove the high practicability and operability of the AEE model in an actual shelter site selection and construction investment, which can achieve the global optimization of evacuation time and the maximization of the use efficiency of the shelters under the financial constraints. It provides a scientific and effective decision-making method for the multi-objective location optimization problem of shelters. Full article
(This article belongs to the Topic Multi-Criteria Decision Making)
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Article
Driver Emotions Recognition Based on Improved Faster R-CNN and Neural Architectural Search Network
Symmetry 2022, 14(4), 687; https://doi.org/10.3390/sym14040687 - 26 Mar 2022
Cited by 1
Abstract
It is critical for intelligent vehicles to be capable of monitoring the health and well-being of the drivers they transport on a continuous basis. This is especially true in the case of autonomous vehicles. To address the issue, an automatic system is developed [...] Read more.
It is critical for intelligent vehicles to be capable of monitoring the health and well-being of the drivers they transport on a continuous basis. This is especially true in the case of autonomous vehicles. To address the issue, an automatic system is developed for driver’s real emotion recognizer (DRER) using deep learning. The emotional values of drivers in indoor vehicles are symmetrically mapped to image design in order to investigate the characteristics of abstract expressions, expression design principles, and an experimental evaluation is conducted based on existing research on the design of driver facial expressions for intelligent products. By substituting a custom-created CNN features learning block with the base 11 layers CNN model in this paper for the development of an improved faster R-CNN face detector that detects the driver’s face at a high frame per second (FPS). Transfer learning is performed in the NasNet large CNN model in order to recognize the driver’s various emotions. Additionally, a custom driver emotion recognition image dataset is being developed as part of this research task. The proposed model, which is a combination of an improved faster R-CNN and transfer learning in NasNet-Large CNN architecture for DER based on facial images, enables greater accuracy than previously possible for DER based on facial images. The proposed model outperforms some recently updated state-of-the-art techniques in terms of accuracy. The proposed model achieved the following accuracy on various benchmark datasets: JAFFE 98.48%, CK+ 99.73%, FER-2013 99.95%, AffectNet 95.28%, and 99.15% on a custom-developed dataset. Full article
(This article belongs to the Topic Multi-Criteria Decision Making)
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Article
Cubic q-Rung Orthopair Hesitant Exponential Similarity Measures for the Initial Diagnosis of Depression Grades
Symmetry 2022, 14(4), 670; https://doi.org/10.3390/sym14040670 - 24 Mar 2022
Abstract
The cubic q-rung orthopair hesitant fuzzy set (Cq-ROHFS) provides greater information and is capable of representing both the interval-valued q-rung orthopair hesitant fuzzy set (IVq-ROHFS) and the q-rung orthopair hesitant fuzzy set (q-ROHFS). The concept of Cq-ROHFS is more flexible when considering the [...] Read more.
The cubic q-rung orthopair hesitant fuzzy set (Cq-ROHFS) provides greater information and is capable of representing both the interval-valued q-rung orthopair hesitant fuzzy set (IVq-ROHFS) and the q-rung orthopair hesitant fuzzy set (q-ROHFS). The concept of Cq-ROHFS is more flexible when considering the symmetry between two or more objects. In social life, complex decision information is often too uncertain and hesitant to allow precision. The cubic q-rung orthopair hesitant fuzzy sets are a useful tool for representing uncertain and hesitant fuzzy information in uncertain decision situations. Using the least common multiple (LCM) extension method, we propose a decision-making method based on an exponential similarity measure and hesitancy in the cubic q-rung orthopair hesitant fuzzy environment. To represent assessment information more accurately, our proposed method adjusts parameters according to the decision maker’s preferences in the decision-making process. The Cq-ROHFS setting was used to develop a depression rating method based on the similarity measure for depressed patients. Finally, the validity and applicability of the decision method is demonstrated using an example of depression rating assessment. As a result of this study, the scientific community can gain insight into real-world clinical diagnostic problems and treatment options. Full article
(This article belongs to the Topic Multi-Criteria Decision Making)
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Article
Translation and Cultural Adaptation into Portuguese of the Quality of Dying and Death Scale for Family Members of Patients in Intensive Care Units
Int. J. Environ. Res. Public Health 2022, 19(6), 3614; https://doi.org/10.3390/ijerph19063614 - 18 Mar 2022
Abstract
The translation and cultural adaptation of the Quality of Dying and Death in Brazil may provide a reliable and reproducible scale for collecting and analyzing data on the process of dying and death, given the absence of Brazilian studies that have produced or [...] Read more.
The translation and cultural adaptation of the Quality of Dying and Death in Brazil may provide a reliable and reproducible scale for collecting and analyzing data on the process of dying and death, given the absence of Brazilian studies that have produced or used scales in this topic. The purpose of this study was to perform the translation and cultural adaptation of the Quality of Dying and Death (QODD 3.2a) scale for intensive care patients’ relatives into Portuguese (Brazil). This methodological study was carried out in a public university of the São Paulo State University (UNESP) medical school, São Paulo, Brazil, in three stages: translation and back-translation by two native-speaking independent professionals, analysis by a committee of specialists, and a pre-test phase. The final version was created by seven experts after making semantic, idiomatic, and cultural changes to 16 items. The results indicated a satisfactory content validation index (CVI ≥ 0.80). This version was applied on 32 relatives of patients who were hospitalized in a public hospital in the interior of São Paulo. No item was excluded from the instrument. The content and face validity were achieved to a satisfactory standard, in addition to reaching the minimum parameters recommended in the literature. The Portuguese version of QODD 3.2a for relatives of deceased patients in intensive care is appropriate and culturally adapted for use in Brazil. Full article
(This article belongs to the Topic Multi-Criteria Decision Making)
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Article
Combining Data Envelopment Analysis and Machine Learning
Mathematics 2022, 10(6), 909; https://doi.org/10.3390/math10060909 - 11 Mar 2022
Cited by 1
Abstract
Data Envelopment Analysis (DEA) is one of the most used non-parametric techniques for technical efficiency assessment. DEA is exclusively concerned about the minimization of the empirical error, satisfying, at the same time, some shape constraints (convexity and free disposability). Unfortunately, by construction, DEA [...] Read more.
Data Envelopment Analysis (DEA) is one of the most used non-parametric techniques for technical efficiency assessment. DEA is exclusively concerned about the minimization of the empirical error, satisfying, at the same time, some shape constraints (convexity and free disposability). Unfortunately, by construction, DEA is a descriptive methodology that is not concerned about preventing overfitting. In this paper, we introduce a new methodology that allows for estimating polyhedral technologies following the Structural Risk Minimization (SRM) principle. This technique is called Data Envelopment Analysis-based Machines (DEAM). Given that the new method controls the generalization error of the model, the corresponding estimate of the technology does not suffer from overfitting. Moreover, the notion of ε-insensitivity is also introduced, generating a new and more robust definition of technical efficiency. Additionally, we show that DEAM can be seen as a machine learning-type extension of DEA, satisfying the same microeconomic postulates except for minimal extrapolation. Finally, the performance of DEAM is evaluated through simulations. We conclude that the frontier estimator derived from DEAM is better than that associated with DEA. The bias and mean squared error obtained for DEAM are smaller in all the scenarios analyzed, regardless of the number of variables and DMUs. Full article
(This article belongs to the Topic Multi-Criteria Decision Making)
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Article
Maritime Environment Assessment and Management Using through Balanced Scorecard by Using DEMATEL and ANP Technique
Int. J. Environ. Res. Public Health 2022, 19(5), 2873; https://doi.org/10.3390/ijerph19052873 - 01 Mar 2022
Cited by 3
Abstract
Previous studies have found that the occurrence of maritime accidents often lacks a sound environment management mechanism. The reason is that maritime safety needs management functions to promote each other. This study aims to assess the risk analysis of maritime accidents, applying balanced [...] Read more.
Previous studies have found that the occurrence of maritime accidents often lacks a sound environment management mechanism. The reason is that maritime safety needs management functions to promote each other. This study aims to assess the risk analysis of maritime accidents, applying balanced scorecard (BSC) concepts integrating decision-making trial and evaluation laboratory (DEMATEL) with analytic network process (ANP). The empirical results are that the balanced scorecard could be applied as a maritime procedure management method in maritime risk analysis. A total of 30 questionnaires were collected via scholar questionnaire, and five criteria or key factors for strengthening risk assessment of marine accidents were determined. According to the application of BSC, the risk analysis criteria constructed can assist maritime authorities to reduce the maritime accidents. Full article
(This article belongs to the Topic Multi-Criteria Decision Making)
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Article
How Does Social Media Influence People to Get Vaccinated? The Elaboration Likelihood Model of a Person’s Attitude and Intention to Get COVID-19 Vaccines
Int. J. Environ. Res. Public Health 2022, 19(4), 2378; https://doi.org/10.3390/ijerph19042378 - 18 Feb 2022
Cited by 2
Abstract
The global COVID-19 mass vaccination program has created a polemic amongst pro- and anti-vaccination groups on social media. However, the working mechanism on how the shared information might influence an individual decision to be vaccinated is still limited. This study embarks on adopting [...] Read more.
The global COVID-19 mass vaccination program has created a polemic amongst pro- and anti-vaccination groups on social media. However, the working mechanism on how the shared information might influence an individual decision to be vaccinated is still limited. This study embarks on adopting the elaboration likelihood model (ELM) framework. We examined the function of central route factors (information completeness and information accuracy) as well as peripheral route factors (experience sharing and social pressure) in influencing attitudes towards vaccination and the intention to obtain the vaccine. We use a factorial design to create eight different scenarios in the form of Twitter posts to test the interaction and emulate the situation on social media. In total, 528 respondents were involved in this study. Findings from this study indicated that both the central route and peripheral route significantly influence individually perceived informativeness and perceived persuasiveness. Consequently, these two factors significantly influence attitude towards vaccination and intention to obtain the vaccine. According to the findings, it is suggested that, apart from evidence-based communication, the government or any interested parties can utilize both experience sharing and social pressure elements to increase engagement related to COVID-19 vaccines on social media, such as Twitter. Full article
(This article belongs to the Topic Multi-Criteria Decision Making)
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Article
Multi-Attribute Decision Making Method for Node Importance Metric in Complex Network
Appl. Sci. 2022, 12(4), 1944; https://doi.org/10.3390/app12041944 - 12 Feb 2022
Cited by 2
Abstract
Correctly measuring the importance of nodes in a complex network is critical for studying the robustness of the network, and designing a network security policy based on these highly important nodes can effectively improve security aspects of the network, such as the security [...] Read more.
Correctly measuring the importance of nodes in a complex network is critical for studying the robustness of the network, and designing a network security policy based on these highly important nodes can effectively improve security aspects of the network, such as the security of important data nodes on the Internet or the hardening of critical traffic hubs. Currently included are degree centrality, closeness centrality, clustering coefficient, and H-index. Although these indicators can identify important nodes to some extent, they are influenced by a single evaluation perspective and have limitations, so most of the existing evaluation methods cannot fully reflect the node importance information. In this paper, we propose a multi-attribute critic network decision indicator (MCNDI) based on the CRITIC method, considering the H-index, closeness centrality, k-shell indicator, and network constraint coefficient. This method integrates the information of network attributes from multiple perspectives and provides a more comprehensive measure of node importance. An experimental analysis of the Chesapeake Bay network and the contiguous USA network shows that MCNDI has better ranking monotonicity, more stable metric results, and is highly adaptable to network topology. Additionally, deliberate attack simulations on real networks showed that the method exhibits high convergence speed in attacks on USAir97 networks and technology routes networks. Full article
(This article belongs to the Topic Multi-Criteria Decision Making)
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Article
The Optimal Strategy of Enterprise Key Resource Allocation and Utilization in Collaborative Innovation Project Based on Evolutionary Game
Mathematics 2022, 10(3), 400; https://doi.org/10.3390/math10030400 - 27 Jan 2022
Abstract
The rational allocation and utilization of key corporate resources is the key to the success of collaborative innovation projects. Finding an optimal strategy for the allocation and utilization of key resources is of great significance for promoting the smooth progress of cooperative both [...] Read more.
The rational allocation and utilization of key corporate resources is the key to the success of collaborative innovation projects. Finding an optimal strategy for the allocation and utilization of key resources is of great significance for promoting the smooth progress of cooperative both innovation parties and increasing project returns. Therefore, from the perspective of the repeated games of the project participants, this article studies the optimal allocation and utilization of key resources of the enterprise in collaborative innovation projects. In this study, nine scenarios and eighteen strategic combinations of resources allocation and utilization by collaborative innovation partners are explored. Explicit expressions for the components of sixteen equilibrium points in terms of parameters are derived. Among these equilibrium points, four stable solutions are determined. These stable solutions correspond to the optimal strategies for enterprises allocating key resources and A&R parties to use these resources in different scenarios, and these strategies enable partners to maximize their interests. On this basis, some suggestions are put forward to promote cooperation and improve project performance. Full article
(This article belongs to the Topic Multi-Criteria Decision Making)
Article
Evaluation Mechanism Design for the Development Level of Urban-Rural Integration Based on an Improved TOPSIS Method
Mathematics 2022, 10(3), 380; https://doi.org/10.3390/math10030380 - 26 Jan 2022
Cited by 6
Abstract
Under the background of new-type urbanization and rural revitalization strategy, how to promote the development of urban–rural integration has become an important issue in today’s society. This paper designed a new evaluation mechanism for the development level of urban–rural integration. Specifically, a three-level [...] Read more.
Under the background of new-type urbanization and rural revitalization strategy, how to promote the development of urban–rural integration has become an important issue in today’s society. This paper designed a new evaluation mechanism for the development level of urban–rural integration. Specifically, a three-level evaluation index system of urban–rural integration development level was established from four aspects: spatial integration, economic integration, social integration and living environment integration. By combining the entropy weight method with the ranking method, a combination weighting method was proposed to determine the weight of each index in the index system. Furthermore, an improved TOPSIS method based on relative entropy and grey relational degree was proposed to evaluate the development level of urban–rural integration, which considering proximity from the perspectives of distance and shape and solving the problem that some situations cannot be compared through the original model. Then, the established evaluation mechanism was applied to make an empirical analysis for evaluating the development level of urban–rural integration in Hubei Province, China. Cluster analysis and obstacle factor analysis were used to further analyze the evaluation results. Finally, according to the evaluation results, some effective countermeasures and policy implications were provided to improve the development level of urban–rural integration in Hubei Province. Full article
(This article belongs to the Topic Multi-Criteria Decision Making)
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Article
Controlling Non-Grain Production Based on Cultivated Land Multifunction Assessment
Int. J. Environ. Res. Public Health 2022, 19(3), 1027; https://doi.org/10.3390/ijerph19031027 - 18 Jan 2022
Cited by 1
Abstract
The control of non-grain production (NGP) has become a great challenge for cultivated land protection in China in recent years. A control method for NGP that can coordinate the conflicts between cultivated land protection and farmers’ interest is urgently needed. Taking Tongxiang City [...] Read more.
The control of non-grain production (NGP) has become a great challenge for cultivated land protection in China in recent years. A control method for NGP that can coordinate the conflicts between cultivated land protection and farmers’ interest is urgently needed. Taking Tongxiang City as an example, this research proposed a solution for the control and management of NGP based on cultivated land multifunctional assessment. The GIS and AHP approach were used to assess production function via a comprehensive evaluation index. The InVEST and FMSPA models were applied to assess ecological function while, the Maxent model was applied to assess recreational function, then multifunctional comprehensive zoning was conducted through natural breakpoint method and spatial overlay analysis. Five development-oriented function zones were considered, including the core area of grain production plus areas for ecological agriculture, leisure agriculture, compound agriculture, and general farmland. Differentiated control measures for NGPs in each functional subarea are proposed considering the current NGP distribution of Tongxiang city. This research can provide a reference for subsequent improvement of land management policies and can aid the achievement of sustainable agricultural development and rural revitalization. Full article
(This article belongs to the Topic Multi-Criteria Decision Making)
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Article
A Novel Approach for Multiplicative Linguistic Group Decision Making Based on Symmetrical Linguistic Chi-Square Deviation and VIKOR Method
Symmetry 2022, 14(1), 136; https://doi.org/10.3390/sym14010136 - 11 Jan 2022
Abstract
Most linguistic-based approaches to multi-attribute group decision making (MAGDM) use symmetric, uniformly distributed sets of additive linguistic terms to express the opinions of decision makers. However, in reality, there are also some problems that require the use of asymmetric, uneven, i.e., non-equilibrium, multiplicative [...] Read more.
Most linguistic-based approaches to multi-attribute group decision making (MAGDM) use symmetric, uniformly distributed sets of additive linguistic terms to express the opinions of decision makers. However, in reality, there are also some problems that require the use of asymmetric, uneven, i.e., non-equilibrium, multiplicative linguistic term sets to express the evaluation. The purpose of this paper is to propose a new approach to MAGDM under multiplicative linguistic information. The aggregation of linguistic data is an important component in MAGDM. To solve this problem, we define a chi-square for measuring the difference between multiplicative linguistic term sets. Furthermore, the linguistic generalized weighted logarithm multiple averaging (LGWLMA) operator and linguistic generalized ordered weighted logarithm multiple averaging (LGOWLMA) operator are proposed based on chi-square deviation. On the basis of the proposed two operators, we develop a novel approach to GDM with multiplicative linguistic term sets. Finally, the evaluation of transport logistics enterprises is developed to illustrate the validity and practicality of the proposed approach. Full article
(This article belongs to the Topic Multi-Criteria Decision Making)
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Article
Characteristics and Outcome Determinants of Hospitalized Older Patients with Cognitive Dysfunction
Int. J. Environ. Res. Public Health 2022, 19(1), 584; https://doi.org/10.3390/ijerph19010584 - 05 Jan 2022
Abstract
Cognitive dysfunction commonly occurs among older patients during admission and is associated with adverse prognosis. This study evaluated clinical characteristics and outcome determinants in hospitalized older patients with cognitive disorders. The main outcomes were length of stay, readmission within 30 days, Barthel index [...] Read more.
Cognitive dysfunction commonly occurs among older patients during admission and is associated with adverse prognosis. This study evaluated clinical characteristics and outcome determinants in hospitalized older patients with cognitive disorders. The main outcomes were length of stay, readmission within 30 days, Barthel index (BI) score at discharge, BI score change (discharge BI score minus BI score), and proportion of positive BI score change to indicate change of activities of daily living (ADL) change during hospitalization. A total of 642 inpatients with a mean age of 79.47 years (76–103 years) were categorized into three groups according to the medical history of dementia, and Mini-Mental State Examination (MMSE) scores at admission. Among them, 74 had dementia diagnosis (DD), 310 had cognitive impairment (CI), and 258 had normal MMSE scores. Patients with DD and CI generally had a higher risk of many geriatric syndromes, such as multimorbidities, polypharmacy, delirium, incontinence, visual and auditory impairment, fall history, physical frailty. They had less BI score, BI score change, and proportion of positive BI score change ADL at discharge. (DD 70.0%, CI 79.0%), suggesting less ADL change during hospitalization compared with those with normal MMSE scores (92.9%; p < 0.001). Using multiple regression analysis, we found that among patients with DD and CI, age (p = 0.008) and walking speed (p = 0.023) were predictors of discharge BI score. In addition, age (p = 0.047) and education level were associated with dichotomized BI score change (positive vs. non-positive) during hospitalization. Furthermore, the number and severity of comorbidities predicted LOS (p < 0.001) and readmission (p = 0.001) in patients with cognitive disorders. It is suggested that appropriate strategies are required to improve clinical outcomes in these patients. Full article
(This article belongs to the Topic Multi-Criteria Decision Making)
Article
Spatial Identification and Redevelopment Evaluation of Brownfields in the Perspective of Urban Complex Ecosystems: A Case of Wuhu City, China
Int. J. Environ. Res. Public Health 2022, 19(1), 478; https://doi.org/10.3390/ijerph19010478 - 02 Jan 2022
Cited by 1
Abstract
Rapid industrialization and urbanization in China have led to a rapid increase in the number of brownfields, however there is a lack of identification of the spatial extent of brownfields in cities and accurate assessment of brownfield redevelopment. Based on the relationship between [...] Read more.
Rapid industrialization and urbanization in China have led to a rapid increase in the number of brownfields, however there is a lack of identification of the spatial extent of brownfields in cities and accurate assessment of brownfield redevelopment. Based on the relationship between brownfields and urban complex ecosystems, this paper defines brownfields in China and constructs a comprehensive evaluation index system including socio-economic and ecological subsystems. Using Wuhu City as empirical evidence, 19 brownfields were identified using remote sensing data and field surveys. Based on the detection of soil contaminants in brownfields, a fuzzy integrated evaluation method was used to suggest their redevelopment direction. It is found that the government’s planned land use types and the brownfield redevelopment evaluation results match to a large extent, but social, economic and ecological environmental factors should be more fully considered. At the same time, the identification and redevelopment of brownfield sites in the city as a whole need to be carried out by the government’s professional forces in order to obtain more effective and scientific conclusions. Full article
(This article belongs to the Topic Multi-Criteria Decision Making)
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Article
Key Concepts of Systemological Approach to CPS Adaptive Information Security Monitoring
Symmetry 2021, 13(12), 2425; https://doi.org/10.3390/sym13122425 - 15 Dec 2021
Cited by 1
Abstract
Modern cyber-physical systems (CPS) use digital control of physical processes. This allows attackers to conduct various cyberattacks on these systems. According to the current trends, an information security monitoring system (ISMS) becomes part of a security management system of CPS. It provides information [...] Read more.
Modern cyber-physical systems (CPS) use digital control of physical processes. This allows attackers to conduct various cyberattacks on these systems. According to the current trends, an information security monitoring system (ISMS) becomes part of a security management system of CPS. It provides information to make a decision and generate a response. A large number of new methods are aimed at CPS security, including security assessment, intrusion detection, and ensuring sustainability. However, as a cyber-physical system operates over time, its structure and requirements may change. The datasets available for the protection object (CPS) and the security requirements have become dynamic. This dynamic effect causes asymmetry between the monitoring data collection and processing subsystem and the presented security tasks. The problem herein is the choice of the most appropriate set of methods in order to solve the security problems of a particular CPS configuration from a particular bank of the available methods. To solve this problem, the authors present a method for the management of an adaptive information security monitoring system. The method consists of solving a multicriteria discrete optimization problem under Pareto-optimality conditions when the available data, methods or external requirements change. The experimental study was performed on an example of smart home intrusion detection. In the study, the introduction of a constraint (a change in requirements) led to the revision of the monitoring scheme and a different recommendation of the monitoring method. As a result, the information security monitoring system gains the property of adaptability to changes in tasks and the available data. An important result from the study is the fact that the monitoring scheme obtained using the proposed management method has a proven optimality under the given conditions. Therefore, the asymmetry between the information security monitoring data collection and processing subsystem and the set of security requirements in cyber-physical systems can be overcome. Full article
(This article belongs to the Topic Multi-Criteria Decision Making)
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Article
Fuzzy Branch-and-Bound Algorithm with OWA Operators in the Case of Consumer Decision Making
Mathematics 2021, 9(23), 3045; https://doi.org/10.3390/math9233045 - 26 Nov 2021
Abstract
The ordered weighted averaging (OWA) operator is one of the most used techniques in the operator’s aggregation procedure. This paper proposes a new assignment algorithm by using the OWA operator and different extensions of it in the Branch-and-bound algorithm. The process is based [...] Read more.
The ordered weighted averaging (OWA) operator is one of the most used techniques in the operator’s aggregation procedure. This paper proposes a new assignment algorithm by using the OWA operator and different extensions of it in the Branch-and-bound algorithm. The process is based on the use of the ordered weighted average distance operator (OWAD) and the induced OWAD operator (IOWAD). We present it as the Branch-and-bound algorithm with the OWAD operator (BBAOWAD) and the Branch-and-bound algorithm with the IOWAD operator (BBAIOWAD). The main advantage of this approach is that we can obtain more detailed information by obtaining a parameterized family of aggregation operators. The application of the new algorithm is developed in a consumer decision-making model in the city of Barcelona regarding the selection of groceries by districts that best suit their needs. We rely on the opinion of local commerce experts in the city. The key advantage of this approach is that we can consider different sources of information independent of each other. Full article
(This article belongs to the Topic Multi-Criteria Decision Making)
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Article
An Ordinal Consistency Indicator for Pairwise Comparison Matrix
Symmetry 2021, 13(11), 2183; https://doi.org/10.3390/sym13112183 - 15 Nov 2021
Cited by 2
Abstract
The pairwise comparison (PC) matrix is often used to manifest human judgments, and it has been successfully applied in the analytic hierarchy process (AHP). As a PC matrix is formed by making paired reciprocal comparisons, symmetry is a striking characteristic of a PC [...] Read more.
The pairwise comparison (PC) matrix is often used to manifest human judgments, and it has been successfully applied in the analytic hierarchy process (AHP). As a PC matrix is formed by making paired reciprocal comparisons, symmetry is a striking characteristic of a PC matrix. It is this simple but powerful means of resolving multicriteria decision-making problems that is the basis of AHP; however, in practical applications, human judgments may be inconsistent. Although Saaty’s rule for the consistency test is commonly accepted, there is evidence that those so-called “acceptable” PC matrices may not be ordinally consistent, which is a necessary condition for a PC matrix to be accepted. We propose an ordinal consistency indicator called SDR (standard deviation of ranks), derive the upper bound of the SDR, suggest a threshold for a decision-maker to assess whether the ordinal consistency of a PC matrix is acceptable, and reveal a surprising fact that the degree of ordinal inconsistency of a small PC matrix may be more serious than a large one. We made a comparative analysis with some other indicators. Experimental results showed that the ordinal inconsistency measured by the SDR is invariant under heterogeneous judgment measurements with a varied spectrum of scales, and that the SDR is superior to the two compared indicators. Note that the SDR not only works for a multiplicative PC matrix but can also be used for additive and fuzzy PC matrices. Full article
(This article belongs to the Topic Multi-Criteria Decision Making)
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