Search Results (1,027)

With the growing popularity of ice sports, indoor ice sports venues are drawing an increasing number of spectators. Maintaining comfort in spectator zones presents a significant challenge for the operational scheduling of climate control systems, which integrate ventilation, heating, and dehumidification functions. To explore economic cost potential while ensuring user comfort, this study proposes a demand response-integrated optimization model for climate control systems. To enhance the model’s practicality and decision-making efficiency, a two-stage optimization method combining multi-objective optimization algorithms with the technique for order preference by similarity to an ideal solution (TOPSIS) is proposed. In terms of algorithm comparison, the performance of three typical multi-objective optimization algorithms—NSGA-II, standard MOEA/D, and Multi-Objective Brown Bear Optimization (MOBBO)—is systematically evaluated. The results show that NSGA-II demonstrates the best overall performance based on evaluation metrics including runtime, HV, and IGD. Simulations conducted in China’s cold regions show that, under comparable comfort levels, schedules incorporating dynamic tariffs are significantly more economically efficient than those that do not. They reduce operating costs by 25.3%, 24.4%, and 18.7% on typical summer, transitional, and winter days, respectively. Compared to single-objective optimization approaches that focus solely on either comfort enhancement or cost reduction, the proposed multi-objective model achieves a better balance between user comfort and economic performance. This study not only provides an efficient and sustainable solution for climate control scheduling in energy-intensive buildings such as ice sports venues but also offers a valuable methodological reference for energy management and optimization in similar settings. Full article

Climate change, resource scarcity, and ecological degradation have become critical bottlenecks constraining socio-economic development. Basin cities serve as key nodes in China’s ecological security pattern, playing indispensable roles in ecological civilization construction. This study established an evaluation index system spanning five dimensions to assess the effectiveness of ecological civilization construction. This study employs the entropy-weighted Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) and Back-Propagation (BP) neural network methods to evaluate the level of ecological civilization construction in the Yellow River Basin from 2010 to 2022, to analyze its indicator weights, and to explore the spatio-temporal evolution characteristics of each city. The results demonstrate the following: (1) Although the ecological civilization construction level of cities in the Yellow River Basin shows a steady improvement, significant regional development disparities persist. (2) The upper reaches are primarily constrained by ecological fragility and economic underdevelopment. The middle reaches exhibit significant internal divergence, with provincial capitals leading yet demonstrating limited spillover effects on neighboring areas. The lower reaches face intense anthropogenic pressures, necessitating greater economic–ecological coordination. (3) Among the dimensions considered, Territorial Space and Eco-environmental Protection emerged as the two most influential dimensions contributing to performance differences. According to the ecological civilization construction performance and changing characteristics of the 48 cities, this study proposes differentiated optimization measures and coordinated development pathways to advance the implementation of the national strategy for ecological protection and high-quality development in the Yellow River Basin. Full article

The gradual recovery of the economy has positioned the digital economy as a vital force driving global economic growth. However, the sustainability of this emerging economic sector is being tested by unexpected systemic shocks. There is a scarcity of research on the factors influencing the sustainable development of the digital economy. Therefore, developing a framework to assess the sustainability of the digital economy is significant. Building on previous research, this study established an evaluation system that extracts key indicators across four dimensions: society, the economy, the environment, and technology. Data were then collected through questionnaires and in-depth interviews with experts. Subsequently, this study employed the fuzzy Decision-Making Trial and Evaluation Laboratory–Analytical Network Process (fuzzy DANP) method to determine the weight of each indicator and used the Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) method to evaluate the sustainability of the digital economy in three cities. Sensitivity analysis was conducted to validate this comprehensive evaluation method. The results indicate that society and the economy are the two most crucial dimensions, while the regional economic development level, enterprise innovation culture, and digital divide are the top three indicators affecting the sustainable development of the digital economy industry. This work suggests that the digital economy industry should enhance regional economic levels, strengthen technological and innovative corporate cultures, and narrow the digital divide to achieve the goal of sustainable development in the digital economy sector. Full article

Model predictive control (MPC) has become a popular method in motor control due to its high adaptability to multivariate control. However, one issue for this control system is constructing a reasonable cost function (CF) and obtaining appropriate weighting factors (WFs) within it. This paper addresses the issue of effectively reducing torque ripple and current harmonic content in permanent magnet synchronous motors (PMSM). Within the three-vector model predictive current control (TV-MPCC) strategy for PMSM, a new CF including current error and switching frequency terms is constructed. Combined with the technique for order preference by similarity to ideal solution (TOPSIS), the optimal control vector is obtained. Compared with traditional methods, this method reduces the complexity of adjusting WFs in the CF. Simulation results show that the motor’s torque ripple and current harmonic content are effectively reduced. Both the steady state and dynamic performance of the PMSM are also improved by means of the proposed multi-objective MPC for current error and switching frequency. Full article

With the increase in the global aging population, the demand for elderly-friendly game products is growing rapidly. To address existing limitations, particularly in user demand extraction and design parameter setting, this study proposed a design framework integrating the BTM–AHP–AD–TOPSIS methods. The goal was to accurately identify the core needs of elderly users and translate them into effective design solutions. User reviews of elderly-friendly game products were collected from e-commerce platforms using Python 3.8-based web scraping. The Biterm Topic Model (BTM) was employed to extract user needs from review texts. These needs were prioritized using the Analytic Hierarchy Process (AHP) and translated into specific design parameters through Axiomatic Design (AD). Finally, the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) was applied to comprehensively evaluate multiple design schemes and select the optimal solution. The results demonstrate that the proposed design path offers a holistic method for progressing from need extraction to design evaluation. It effectively overcomes previous limitations, including inefficient need extraction, limited scope, unclear need weighting, and unreasonable design parameters. This method enhances user acceptance and satisfaction while establishing rigorous design processes and scientific evaluation standards, making it well suited for developing elderly-friendly products. Full article

In order to promote the green and low-carbon transformation of the economy and society, as the economic center of the western region of China, Chengdu actively promotes the national green and low-carbon policies. Some specific measures are proposed to develop Chengdu’s low-carbon economy, such as increasing the ownership of new energy vehicles, promoting the development of park cities and increasing the proportion of clean energy and non-fossil energy, etc. So, in order to accurately evaluate Chengdu’s low-carbon economy-development achievements, firstly, this paper uses literature research to construct an evaluation indicator system for the low-carbon economy development of Chengdu city from five dimensions: economy, energy, technology, environment, and transportation. Then, an improved Analytic Hierarchy Process (AHP) method based on judgment matrices is proposed to determine subjective weights of indicators, while Entropy Weight Method (EWM) and Variation Coefficient (VC) method are used to determine objective weights of the evaluation indicators. Finally, the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) is used for the multi-indicator comprehensive evaluation of Chengdu’s low-carbon economy development. The evaluation results show that the comprehensive performance of Chengdu’s low-carbon economy has continued to improve from 2018 to 2023, simultaneously, the main influencing factors and weak links are analyzed, and targeted suggestions and strategies for improvement are put forward to promote the low-carbon economy development of Chengdu city. Full article

This paper presents a multi-criteria decision-making (MCDM) approach for optimizing a microgrid system to achieve Plus-Energy Building (PEB) performance at the University of Coimbra’s Electrical Engineering Department. Using Python 3.12.8, Rhino 7, and PVsyst 8.0.1, simulations considered architectural and visual constraints, with economic feasibility assessed through a TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) analysis. The system is projected to generate approximately 1 GWh annually, with a 98% probability of exceeding 1076 MWh based on Gaussian estimation. Consumption is estimated at 460 MWh, while a 3.8 MWh battery ensures up to 72 h of autonomy. Rooftop panels and green parking arrays, fixed at 13.5° and 59°, minimize visual impact while contributing a surplus of +160% energy injection (or a net surplus of +60% energy after self-consumption). Assuming a battery cost of EUR 200/kWh, each hour of energy storage for the building requires 61 kWh of extra capacity with a cost of 12,200 (EUR/hr.storage). Recognizing environmental variability, these figures represent cross-validated probabilistic estimates derived from both PVsyst and Monte Carlo simulation using Python, reinforcing confidence in system feasibility. A holistic photovoltaic optimization strategy balances technical, economic, and architectural factors, demonstrating the potential of PEBs as a sustainable energy solution for academic institutions. Full article

Climate change, the consequences of which have been more intense than ever in the last few decades, makes the need for sustainable transportation even more imperative. The promotion of public transportation and the discouragement of private car use are among the main priorities of sustainable transport planning in modern urban areas. However, the selection of the most appropriate transport project, apart from significant opportunities, is also accompanied by significant challenges, especially under the demand of compromising—often conflicting—social, environmental, and economic criteria, as well as different stakeholders’ interests. The aim of the present paper is to provide decision analysts and policy-makers with a decision-support tool for the prioritization and optimum selection of public transport projects for an urban area within the framework of sustainability. For this purpose, a comprehensive inventory of criteria for the evaluation of urban public transport systems (alternatives), along with a standardized table with the relevant performance of the most common alternatives (i.e., metro, tram, monorail, and BRT) are provided based on international literature review. A multi-criteria decision-aiding methodology based on TOPSIS (Technique for Order Preference by Similarity to Ideal Solution), allowing for the direct exclusion of an alternative not meeting certain “binding” criteria from further evaluation, thus saving time, effort and cost, taking into account different stakeholders’ interests and preferences, as well as the particularities and special characteristics of the study area, is then proposed and tested through a theoretical case study. Full article

Against the backdrop of frequent public health emergencies caused by infectious diseases, it is urgent to evaluate the importance of urban epidemic prevention by integrating population mobility networks. In this study, a comprehensive evaluation index system is constructed based on a population mobility network, and the improved entropy weight method and analytic hierarchy process are used to obtain the comprehensive weights. The weight imbalance problem of traditional methods is solved by introducing community structure weighting and subjective weight. We establish a Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS)-based evaluation model named city importance evaluation based on the division of communities and TOPSIS (CICT) for the importance of urban epidemic prevention and simulate the model using data from 297 cities in China. It can rank indicators that affect the importance of cities in infectious disease prevention and control and identify key cities for infectious disease prevention and control. The influence of various indicators on the evaluation objectives vary during different investigation periods, but the entropy weights of confirmed cases, hospital beds, and practicing (assistant) physicians remain at a high level. Cities with a high number of confirmed cases consistently rank at the top in the comprehensive evaluation, but this model can also identify potential key cities with fewer confirmed cases. These cities require key management during the outbreak of infectious diseases. The evaluation model can scientifically assess the epidemic prevention significance of cities, improve the efficiency of public health emergency management, and provide quantitative support for formulating urban epidemic control strategies, promoting resource optimization allocation, and implementing targeted measures. Full article

To explore how varying viewpoints influence the accuracy of distributed fusion in asynchronous, nonlinear visual-field systems, this study investigates fusion strategies for multi-target tracking. The primary focus is on how different sensor perspectives affect the fusion of nonlinear moving-target data and the spatial segmentation of such targets. We propose a differential-view nonlinear multi-target tracking approach that integrates the Gaussian mixture, jump Markov nonlinear system, and the cardinalized probability hypothesis density (GM-JMNS-CPHD). The method begins by partitioning the observation space based on the boundaries of distinct viewpoints. Next, it applies a combined technique—the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) and SOS (stochastic outlier selection)—to identify outliers near these boundaries. To achieve accurate detection, the posterior intensity is split into several sub-intensities, followed by reconstructing the multi-Bernoulli cardinality distribution to model the target population in each subregion. The algorithm’s computational complexity remains on par with the standard GM-JMNS-CPHD filter. Simulation results confirm the proposed method’s robustness and accuracy, demonstrating a lower error rate compared to other benchmark algorithms. Full article

With the deterioration of the global climate, the losses caused by distribution network failures during natural disasters such as typhoons have become increasingly serious. In the whole process of disaster resistance, it is very important to effectively identify the weak links in distribution networks during typhoon disasters. In this paper, the weak links in distribution networks during typhoons are identified dynamically from four indexes: real-time failure rate, load loss caused by line disconnection, line degree, and line betweenness. First, the Batts typhoon model is established to simulate the whole process of the typhoon and obtain the real-time failure rate of the distribution network. Secondly, the distribution network is powered by distributed generators when there are line disconnections, and a mixed integer linear programming model is established to solve the problem. Then, the line degrees and the line betweenness are calculated to obtain the structure indexes of the line, both of which are dynamically related to the power flow and the loads of the distribution network. Finally, the four indexes are comprehensively analyzed, and the dynamic identification of the weak links in the distribution network are realized by the analytic hierarchy process (AHP)—entropy weight (EW)—technique for order preference by similarity to an ideal solution (TOPSIS) method. The results of the case study show that the proposed method can effectively identify the weak links in a distribution network during a typhoon and provide a reference to resist extreme disasters. Full article

Additive manufacturing (AM) has been gaining increased traction in the manufacturing industry due to its ability to fabricate prototypes and end use parts in low volumes at a much lower cost compared to conventional manufacturing processes. There has been research to select an AM process appropriate for fabricating particular parts. However, there is little extant research to select appropriate AM machines even though there is a growing number of AM machines with interesting topologies, structures, and systems. This paper proposes a methodology that aims to assist Technical Experts in selecting a machine for Fused Filament Fabrication (FFF). The methodology is built around a weighted Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), which uses the concept of relative closeness and attribute weights to rank the machines. The paper uses Monte Carlo simulations for sensitivity analysis to evaluate the impact of randomizing attribute scoring, perturbing weights assigned, and probability distributions used to model human decision variability. The methodology and the sensitivity analysis were applied to three case studies, with five FFF machines and seven attributes, and top machines ranked for a specific part were found to be largely robust. Full article

In this study, the authors present the results of a systematic literature review on applications of the technique for order of preference by similarity to ideal solution (TOPSIS) in power systems. The preferred reporting items for systematic reviews and meta-analyses (PRISMA) approach was used in the identification of publications used in this research. The SCOPUS database was utilized to locate the publication, and a total of 78 articles published between 2014 and 2024 were included in the review. A bibliometric analysis was performed, and reports were given on the annual number of publications and the top 10 cited journals. The main themes emerging from the content review of the publications were types of TOPSIS approaches, calculation of weights in multi-criteria decision-making (MCDM) problems, energy markets applications, renewable energy technologies assessment, heating and cooling systems combined with power systems, power system operation strategies, power system stability assessment, power system operations planning, and other power systems applications. Research trends and developments in the area were analyzed to identify the existing gaps. Proposed future research areas were identified based on trends and gaps presented. Full article

Multi-criteria Decision Making (MCDM) presents a novel approach towards truly holistic green sustainability, particularly within the context of chemical process plants (CPPs). ASPEN Plus v12.0 was utilised for two representative CPP cases: isopropanol (IPA) production via isopropyl acetate, and green ammonia (NH₃) production. An integrated Fuzzy Analytic Hierarchy Process (FAHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) was modelled in MATLAB v24.1 to prioritise the holistically green and sustainable pathways. Life cycle assessments (LCAs) were employed to select the pathways, and the most suitable sub-criteria per the four criteria are as follows: social, economic, environmental, and technical. In descending order of optimality, the pathways were ranked as follows for green NH₃ and IPA, respectively: Hydropower (HPEA) > Wind Turbine (WGEA) > Biomass Gasification (BGEA)/Solar Photovoltaic (PVEA) > Nuclear High Temperature (NTEA), and Propylene Indirect Hydration (IAH) > Direct Propylene Hydration (PH) > Acetone Hydrogenation (AH). Sensitivity analysis evaluated the FAHP–TOPSIS framework to be overall robust. However, there are potential uncertainties within and/or among sub-criteria, particularly in the social dimension, due to software and data limitations. Future research would seek to integrate FAHP with VIKOR and the Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE-II). Full article

Rural areas are experiencing significant changes in socio-economic and spatial patterns, and research on the characteristics of rural restructuring is conducive to the planning of rural revitalization. However, few studies have focused on the changes in regional development imbalances in the process of rural restructuring. This study aims to explore whether rural restructuring mitigates or exacerbates existing regional disparities, and to assess the degree of coordination among economic, social, and spatial restructuring dimensions. In this study, the evolution of spatio-temporal patterns and divergence characteristics of unevenly developed regions in the process of rural restructuring from 2010 to 2020 were investigated by using the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) model and the coupled coordination model. We found the following: (1) The level of rural development has increased significantly and the overall pattern has not changed. Meanwhile, the degree of regional imbalance has deepened, evolving from a low level of disequilibrium to a pattern of high levels but more pronounced spatial polarization. (2) The impacts of different dimensions of rural restructuring on regional imbalance are not consistent, and the social and spatial dimensions are significantly more unbalanced than the economic dimension. (3) The analysis of the driving mechanism shows that there are significant spatial and temporal differences between a variety of driving factors, the strength of their role, positive and negative have evolved in stages, and the transition from a government-led to a market-driven trend is gradually obvious. In the future, rural planning should pay more attention to resource inputs in the social and spatial dimensions, and improve the equilibrium of the social and spatial dimensions, which is more conducive to mitigating the trend of regional polarization. Full article