Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
4.0
2.3
Journals
Mathematics
Special Issues
Multi-attribute Decision Making and Intelligent Computing in Smart Governance
share announcement

Multi-attribute Decision Making and Intelligent Computing in Smart Governance

A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "D2: Operations Research and Fuzzy Decision Making".

Deadline for manuscript submissions: 30 June 2025 | Viewed by 7277

Special Issue Editor

Dr. Liguo Fei

E-Mail Website
Guest Editor
School of Political Science and Public Administration, Shandong University, Qingdao 266237, China
Interests: multi-attribute decision making; Dempster-Shafer theory; multi-sensor information fusion; emergency management; urban safety; uncertainty modeling

Special Issue Information

Dear Colleagues,

We are pleased to announce this Special Issue of the journal Mathematics entitled “Multi-Attribute Decision Making and Intelligent Computing in Smart Governance”. This initiative focuses on the theoretical and practical progress of multi-attribute decision making and intelligent computing methods, with special attention on their innovative applications in the field of smart governance. The progress of methods and technology has brought about this type of governance, especially in the digital age, where new solutions to problems have emerged in the field of public administration. This Special Issue will focus on the development of multi-attribute decision making and intelligent computing methods, while also focusing on their applications in areas such as risk governance, digital governance, emergency management, and smart cities.

Dr. Liguo Fei
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Mathematics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • multi-attribute decision-making method in a linguistic environment
  • multi-attribute decision-making method in a fuzzy environment
  • multi-attribute decision-making method based on the Dempster–Shafer theory
  • multi-attribute decision-making method in a probabilistic environment
  • applications of multi-attribute decision making and intelligent computing methodologies in multi-sensor information fusion
  • applications of multi-attribute decision making and intelligent computing methodologies in risk decisions
  • applications of multi-attribute decision making and intelligent computing methodologies in smart cities
  • applications of multi-attribute decision making and intelligent computing methodologies in emergency management
  • applications of multi-attribute decision making and intelligent computing methodologies in disaster prevention and reduction
  • applications of multi-attribute decision making and intelligent computing methodologies in digital governance

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

Further information on MDPI's Special Issue policies can be found here.

Published Papers (6 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

Jump to: Review

15 pages, 303 KiB  
Article
Information Fusion and Decision-Making Utilizing Additional Permutation Information
by Meizhu Li, Linshan Li and Qi Zhang
Mathematics 2024, 12(22), 3632; https://doi.org/10.3390/math12223632 - 20 Nov 2024
Cited by 1 | Viewed by 810
Abstract
The theory of multi-source information fusion plays a pivotal role in decision-making, especially when handling uncertain or imprecise information. Among the existing frameworks, evidence theory has proven effective for integrating diverse information sources to support informed decision-making. Recently, Random Permutation Set Theory (RPST), [...] Read more.
The theory of multi-source information fusion plays a pivotal role in decision-making, especially when handling uncertain or imprecise information. Among the existing frameworks, evidence theory has proven effective for integrating diverse information sources to support informed decision-making. Recently, Random Permutation Set Theory (RPST), an extension of evidence theory, has shown significant practical value due to its ability to leverage the additional information inherent in event permutations. This insight inspires the utilization of permutation data to enhance the decision-making process. When employing RPST for decision-making and fusion, the order in which the fusion is performed can substantially influence the final results. To address this issue, we propose a novel approach that utilizes Fisher Scores to extract additional permutation information to guide decision-making within the RPST framework. Experimental results on the Iris dataset validate the feasibility and effectiveness of the proposed method. Compared to fusion methods employing weighted averaging, our approach, which leverages additional information to determine the fusion order, demonstrates superior accuracy across various training set proportions, achieving an accuracy of 96.26% at an 80% training set proportion. This provides an enhanced strategy for decision-making under uncertainty. Full article
(This article belongs to the Special Issue Multi-attribute Decision Making and Intelligent Computing in Smart Governance)
►▼ Show Figures

Figure 1

30 pages, 5179 KiB  
Article
How Do We Analyze the Accident Causation of Shield Construction of Water Conveyance Tunnels? A Method Based on the N-K Model and Complex Network
by Yong Zhang, Qi Zhang, Xiang Zhang, Meng Li and Guoqing Qi
Mathematics 2024, 12(20), 3222; https://doi.org/10.3390/math12203222 - 15 Oct 2024
Cited by 1 | Viewed by 911
Abstract
In the construction of water conveyance tunnels with the shield method, accidents have occurred from time to time, such as collapses and explosions, and it is of practical significance to explore the cause mechanism of the accident. However, previous research has not considered [...] Read more.
In the construction of water conveyance tunnels with the shield method, accidents have occurred from time to time, such as collapses and explosions, and it is of practical significance to explore the cause mechanism of the accident. However, previous research has not considered the effects of dependence between risks on the risk spread. In response, we propose a method based on the Natural Killing Model (the N-K Model) and complex network theory to analyze the cause of shield construction accidents in water conveyance tunnels. By deeply exploring the transmission mechanism and action intensity between system risks, this method can scientifically clarify the accident cause mechanism and provide support for engineering construction safety management. The method constructs a risk index system. Secondly, we introduce the N-K model to reveal the risk coupling mechanism. Then, based on complex network theory, we construct the incident causation model and revise the node’s centrality with the coupling value. Finally, the network topology parameters are calculated to quantitatively describe the causal characteristics of accidents, revealing the risk evolution process and critical causes. The research results indicate that the key causes of accidents are failure to construct according to regulations, inadequate emergency measures, poor ability of judgment and decision-making, and insufficient understanding of abnormal situations. The front end of critical links is subject to human or management risks and should be carefully controlled during construction. Full article
(This article belongs to the Special Issue Multi-attribute Decision Making and Intelligent Computing in Smart Governance)
►▼ Show Figures

Figure 1

23 pages, 3593 KiB  
Article
An Improved Laplacian Gravity Centrality-Based Consensus Method for Social Network Group Decision-Making with Incomplete ELICIT Information
by Jinjing Mao, Xiangjie Gou and Zhen Hua
Mathematics 2024, 12(13), 2013; https://doi.org/10.3390/math12132013 - 28 Jun 2024
Cited by 1 | Viewed by 973
Abstract
With the advancement of information technology, social media has become increasingly prevalent. The complex networks of social relationships among decision-makers (DMs) have given rise to the problem of social network group decision-making (SNGDM), which has garnered considerable attention in recent years. However, most [...] Read more.
With the advancement of information technology, social media has become increasingly prevalent. The complex networks of social relationships among decision-makers (DMs) have given rise to the problem of social network group decision-making (SNGDM), which has garnered considerable attention in recent years. However, most existing consensus-reaching methods in SNGDM only consider local network information when determining the influence of DMs within the social network. This approach fails to adequately reflect the crucial role of key DMs in regulating information propagation during the consensus-reaching process. Additionally, the partial absence of linguistic evaluations in the decision-making problems also poses obstacles to identifying the optimal alternative. Therefore, this paper proposes an improved Laplacian gravity centrality-based consensus method that can effectively handle incomplete decision information in social network environments. First, the extended comparative linguistic expressions with symbolic translation (ELICIT) are utilized to describe DMs’ linguistic evaluations and construct the incomplete decision matrix. Second, the improved Laplacian gravity centrality (ILGC) is proposed to quantify the influence of DMs in the social network by considering local and global topological structures. Based on the ILGC measure, we develop a trust-driven consensus-reaching model to enhance group consensus, which can better simulate opinion interactions in real-world situations. Lastly, we apply the proposed method to a smart city evaluation problem. The results show that our method can more reasonably handle incomplete linguistic evaluations, more comprehensively capture the influence of DMs, and more effectively improve group consensus. Full article
(This article belongs to the Special Issue Multi-attribute Decision Making and Intelligent Computing in Smart Governance)
►▼ Show Figures

Figure 1

17 pages, 904 KiB  
Article
A Multi-Information Dissemination Model Based on Cellular Automata
by Changheng Shao, Fengjing Shao, Xin Liu, Dawei Yang, Rencheng Sun, Lili Zhang and Kaiwen Jiang
Mathematics 2024, 12(6), 914; https://doi.org/10.3390/math12060914 - 20 Mar 2024
Cited by 5 | Viewed by 1710
Abstract
Significant public opinion events often trigger pronounced fluctuations in online discourse. While existing models have been extensively employed to analyze the propagation of public opinion, they frequently overlook the intricacies of information dissemination among heterogeneous users. To comprehensively address the implications of public [...] Read more.
Significant public opinion events often trigger pronounced fluctuations in online discourse. While existing models have been extensively employed to analyze the propagation of public opinion, they frequently overlook the intricacies of information dissemination among heterogeneous users. To comprehensively address the implications of public opinion outbreaks, it is crucial to accurately predict the evolutionary trajectories of such events, considering the dynamic interplay of multiple information streams. In this study, we propose a SEInR model based on cellular automata to simulate the propagation dynamics of multi-information. By delineating information dissemination rules that govern the diverse modes of information propagation within the network, we achieve precise forecasts of public opinion trends. Through the concurrent simulation and prediction of multi-information game and evolution processes, employing Weibo users as nodes to construct a public opinion cellular automaton, our experimental analysis reveals a significant similarity exceeding 98% between the proposed model and the actual user participation curve observed on the Weibo platform. Full article
(This article belongs to the Special Issue Multi-attribute Decision Making and Intelligent Computing in Smart Governance)
►▼ Show Figures

Figure 1

25 pages, 941 KiB  
Article
Project Group Program Generation and Decision Making Method Integrating Coupling Network and Hesitant Fuzzy
by Liwei Qian, Yajie Dou, Chang Gong, Xiangqian Xu and Yuejin Tan
Mathematics 2023, 11(18), 4010; https://doi.org/10.3390/math11184010 - 21 Sep 2023
Viewed by 1227
Abstract
Modern urban construction relies on a large number of projects. Project groups are an effective way to manage a large number of projects. In view of the current lack of scientific methods for constructing and evaluating project group programs, which are mainly based [...] Read more.
Modern urban construction relies on a large number of projects. Project groups are an effective way to manage a large number of projects. In view of the current lack of scientific methods for constructing and evaluating project group programs, which are mainly based on subjective experience, this article proposes a scientific method for project group program generation and decision-making. The method proposed in this article applies a multi-layer coupling network to the modeling of project groups and divides projects into planning projects and execution projects to form a heterogeneous coupling network. Then, starting from the principle of project information dissemination, the evaluation indicators of the project group program were defined, and finally, the hesitant fuzzy decision-making method was used to assist in decision making. This article can provide a new method for project group construction and management, and provide strong support for the construction of smart cities and digital governments. Full article
(This article belongs to the Special Issue Multi-attribute Decision Making and Intelligent Computing in Smart Governance)
►▼ Show Figures

Figure 1

Review

Jump to: Research

45 pages, 17561 KiB  
Review
Application of Multiple-Criteria Decision-Making Technology in Emergency Decision-Making: Uncertainty, Heterogeneity, Dynamicity, and Interaction
by Tao Li, Jiayi Sun and Liguo Fei
Mathematics 2025, 13(5), 731; https://doi.org/10.3390/math13050731 - 24 Feb 2025
Viewed by 715
Abstract
With the increasing frequency of natural and man-made disasters, emergency management has become a key research field aimed at saving lives and reducing environmental and economic losses. As the core link in responding to sudden crisis events, emergency decision-making is directly related to [...] Read more.
With the increasing frequency of natural and man-made disasters, emergency management has become a key research field aimed at saving lives and reducing environmental and economic losses. As the core link in responding to sudden crisis events, emergency decision-making is directly related to the stability of society, the safety of citizens, and the robustness of infrastructure. As a scientific method, multiple-criteria decision-making (MCDM) technology has gradually become an important tool for solving complex decision-making problems in emergency management. It can handle the uncertainty, heterogeneity, dynamicity, and interaction in emergencies and select the best alternative or rank all options for multiple reference attributes in a limited number of options to solve decision-making problems. This paper comprehensively reviews the existing relevant literature, analyzes the current status and challenges of MCDM technology in its application process and in emergency management, and proposes research gaps and development directions in this field. Full article
(This article belongs to the Special Issue Multi-attribute Decision Making and Intelligent Computing in Smart Governance)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-6
Back to TopTop