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Applied Sciences
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Fuzzy Control Systems: Latest Advances and Prospects
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Fuzzy Control Systems: Latest Advances and Prospects

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".

Deadline for manuscript submissions: 10 November 2024 | Viewed by 7055

Special Issue Editor

Prof. Dr. Yiming Tang

E-Mail Website
Guest Editor
School of Computer and Information, Hefei University of Technology, Hefei, China
Interests: fuzzy control; fuzzy reasoning; clustering; fuzzy systems; machine learning; image processing; affective computing; granular computing; computer-aided design

Special Issue Information

Dear Colleagues,

As a branch of modern control theory, fuzzy control plays a very important role today. In recent years, it has achieved relatively long-term development. It has not only played an important role in industry, national defense, medicine, prediction, engineering design, information processing, and sociology, but has also led to rapid development in the fields of environmental protection and energy conservation, psychology and finance. Cloud model theory is also a branch of fuzzy control arising in the field of artificial intelligence in the past decade, and has made considerable progress in the field of virtual reality and intelligent control. In addition, fuzzy reasoning is one of the core aspects of fuzzy control. Fuzzy reasoning plays an important role in fuzzy logic, affective computing, machine learning, image processing, granularity computing, collaborative computing and other fields.

This Special Issue aims to explore new progress in fuzzy control systems, including theoretical and practical innovation.

Prof. Dr. Yiming Tang
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. Applied Sciences 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 2400 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

  • fuzzy control
  • fuzzy reasoning
  • fuzzy sets
  • collaborative computing
  • machine learning
  • affective computing
  • image processing
  • granular computing

Published Papers (6 papers)

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Research

17 pages, 1454 KiB  
Article
Linguistic Interval-Valued Spherical Fuzzy Soft Set and Its Application in Decision Making
by Tie Hou, Zheng Yang, Yanling Wang, Hongliang Zheng, Li Zou and Luis Martínez
Appl. Sci. 2024, 14(3), 973; https://doi.org/10.3390/app14030973 - 23 Jan 2024
Viewed by 515
Abstract
Under uncertain environments, how to characterize individual preferences more naturally and aggregate parameters better have been hot research topics in multiple attribute decision making (MADM). Fuzzy set theory provides a better mathematical tool to deal with uncertain data, which promotes substantial extended studies. [...] Read more.
Under uncertain environments, how to characterize individual preferences more naturally and aggregate parameters better have been hot research topics in multiple attribute decision making (MADM). Fuzzy set theory provides a better mathematical tool to deal with uncertain data, which promotes substantial extended studies. In this paper, we propose a hybrid fuzzy set model by combining a linguistic interval-valued spherical fuzzy set with a soft set for MADM. The emergence of a linguistic interval-valued spherical fuzzy soft set (LIVSFSS) not only handles qualitative information and provides more freedom to decision makers, but also solves the inherent problem of insufficient parameterization tools for fuzzy set theory. To tackle the application challenges, we introduce the basic concepts and define some operations of LIVSFSS, e.g., the “complement”, the “AND”, the “OR”, the “necessity”, the “possibility” and so on. Subsequently, we prove De Morgan’s law, associative law, distribution law for operations on LIVSFSS. We further propose the linguistic weighted choice value and linguistic weighted overall choice value for MADM by taking parameter weights into account. Finally, the MADM algorithm and parameter reduction algorithm are provided based on LIVSFSS, together with examples and comparisons with some existing algorithms to illustrate the rationality and effectiveness of the proposed algorithms. Full article
(This article belongs to the Special Issue Fuzzy Control Systems: Latest Advances and Prospects)
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24 pages, 1304 KiB  
Article
Structured Life Narratives: Building Life Story Hierarchies with Graph-Enhanced Event Feature Refinement
by Fang Gui, Jiaoyun Yang, Yiming Tang, Hongtu Chen and Ning An
Appl. Sci. 2024, 14(2), 918; https://doi.org/10.3390/app14020918 - 22 Jan 2024
Viewed by 754
Abstract
The life stories of older adults encapsulate an array of personal experiences that reflect their care needs. However, due to inherent fuzzy features, fragmented natures, repetition, and redundancies, the practical application of the life story approach poses challenges for caregivers in acquiring and [...] Read more.
The life stories of older adults encapsulate an array of personal experiences that reflect their care needs. However, due to inherent fuzzy features, fragmented natures, repetition, and redundancies, the practical application of the life story approach poses challenges for caregivers in acquiring and comprehending these narratives. Addressing this challenge, our study introduces a novel approach called Life Story Hierarchies with Graph-Enhanced Event Feature Refinement (LSH-GEFR). LSH-GEFR constructs a bilayer graph. Firstly, the event element map leverages intricate relationships between event elements to extract environmental features, providing a detailed context for understanding each event element. Secondly, the event map explores the complex web of relationships between the events themselves, allowing LSH-GEFR to generate a comprehensive understanding of each event and enhance its representation. Subsequently, we conducted experiments on different datasets and found that, in comparison with four advanced event tree generation methods, the proposed LSH-GEFR method outperformed them in terms of path coherence, branch reasonableness, and overall readability when generating life story hierarchies. Over 84.91% of the structured life narratives achieved readability, marking a 5.96% increase over the best-performing approach at the baseline. Full article
(This article belongs to the Special Issue Fuzzy Control Systems: Latest Advances and Prospects)
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14 pages, 1125 KiB  
Article
Ranking Strategic Goals with Fuzzy Entropy Weighting and Fuzzy TOPSIS Methods: A Case of the Scientific and Technological Research Council of Türkiye
by Betül Cansu Öztürk and Hadi Gökçen
Appl. Sci. 2023, 13(14), 8060; https://doi.org/10.3390/app13148060 - 10 Jul 2023
Cited by 1 | Viewed by 942
Abstract
This study involves an integrated approach consisting of the Fuzzy AEW Method which considers all relevant criteria and involves the contribution of all members of a strategic planning team in the determination of strategic goals as well as the Fuzzy Technique for Order [...] Read more.
This study involves an integrated approach consisting of the Fuzzy AEW Method which considers all relevant criteria and involves the contribution of all members of a strategic planning team in the determination of strategic goals as well as the Fuzzy Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) method. The Fuzzy AEW method has been used in weighing the criteria whereas the Fuzzy TOPSIS method has been used in determining the order of the alternatives. This article presents a real-world case using this model in setting targets for improving the institutional capacity of the Scientific and Technological Research Council of Türkiye (TÜBITAK). In this study, strategic goals have been set forth considering the opinion of strategic planning experts and previous strategic plans, and then the said method has been applied. The model could easily be applied both in the public and private sectors. This new model involves the effective planning of scarce resources and ensures digitalization in planning as well as the determination of goals through analytical methods. Ineffective meetings and workshops of the past will be replaced by a participatory and transparent structure. Full article
(This article belongs to the Special Issue Fuzzy Control Systems: Latest Advances and Prospects)
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17 pages, 5888 KiB  
Article
Construction of a Dynamic Diagnostic Approach for a Fuzzy-Interval Petri Network
by Fatma Lajmi, Mostafa Rashdan, Bilel Neji, Raymond Ghandour and Hedi Dhouibi
Appl. Sci. 2023, 13(13), 7603; https://doi.org/10.3390/app13137603 - 27 Jun 2023
Viewed by 751
Abstract
Fault diagnosis plays a crucial role in enhancing system dependability and minimizing potential catastrophic consequences for both equipment and human safety. This article presents a research study focused on developing a diagnosis and control approach for discrete event systems using the Petri net [...] Read more.
Fault diagnosis plays a crucial role in enhancing system dependability and minimizing potential catastrophic consequences for both equipment and human safety. This article presents a research study focused on developing a diagnosis and control approach for discrete event systems using the Petri net Fuzzy Interval (IFPN). The Petri net is utilized as a modeling tool for the target system. The paper describes a case study conducted on an ingredient mixing system, where the objective is to maintain the concentration of ingredients within a valid range. A diagnostic framework is constructed and successfully applied to identify faults in the system. The proposed approach is further validated through simulation tests conducted on a mixing system. Full article
(This article belongs to the Special Issue Fuzzy Control Systems: Latest Advances and Prospects)
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25 pages, 1981 KiB  
Article
A Facility Layout Algorithm for Logistics Scenarios Driven by Transport Lines
by Fulin Jiang, Lin Li, Yiming Tang, Hailong Zhang and Xiaoping Liu
Appl. Sci. 2023, 13(12), 7215; https://doi.org/10.3390/app13127215 - 16 Jun 2023
Cited by 1 | Viewed by 1545
Abstract
The layout of facilities in a logistics scenario involves not only the working facilities responsible for processing materials but also the transport lines responsible for transporting materials. The traditional facility layout methods do not take into account the transportation facilities nor calculate the [...] Read more.
The layout of facilities in a logistics scenario involves not only the working facilities responsible for processing materials but also the transport lines responsible for transporting materials. The traditional facility layout methods do not take into account the transportation facilities nor calculate the material handling cost by Manhattan distance, thus failing to fulfill the actual requirements of industrial logistics scenarios. In this paper, a facility layout algorithm framework MOSA-FD driven by transport lines is proposed. A multi-objective simulated annealing (MOSA) algorithm is designed for both material handling cost (MHC) and transport facility cost (TFC) objectives. Then, a force-directed (FD) algorithm is applied to correct the unreasonable solutions according to the material transport lines in the logistics workshop, and a better solution is quickly obtained. Finally, by comparing the results with those of other metaheuristic multi-objective algorithms, the acceleration of the force-directed algorithm in this layout problem is demonstrated in experimental instances of different scales, and our method, compared to the MOSA algorithm, can reach optimal ratios of 36% and 80%, respectively, on the multi-objective. Full article
(This article belongs to the Special Issue Fuzzy Control Systems: Latest Advances and Prospects)
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28 pages, 1917 KiB  
Article
VSFCM: A Novel Viewpoint-Driven Subspace Fuzzy C-Means Algorithm
by Yiming Tang, Rui Chen and Bowen Xia
Appl. Sci. 2023, 13(10), 6342; https://doi.org/10.3390/app13106342 - 22 May 2023
Cited by 2 | Viewed by 1033
Abstract
Nowadays, most fuzzy clustering algorithms are sensitive to the initialization results of clustering algorithms and have a weak ability to handle high-dimensional data. To solve these problems, we developed the viewpoint-driven subspace fuzzy c-means (VSFCM) algorithm. Firstly, we propose a new cut-off distance. [...] Read more.
Nowadays, most fuzzy clustering algorithms are sensitive to the initialization results of clustering algorithms and have a weak ability to handle high-dimensional data. To solve these problems, we developed the viewpoint-driven subspace fuzzy c-means (VSFCM) algorithm. Firstly, we propose a new cut-off distance. Based on this, we establish the cut-off distance-induced clustering initialization (CDCI) method and use it as a new strategy for cluster center initialization and viewpoint selection. Secondly, by taking the viewpoint obtained by CDCI as the entry point of knowledge, a new fuzzy clustering strategy driven by knowledge and data is formed. Based upon these, we put forward the VSFCM algorithm combined with viewpoints, separation terms, and subspace fuzzy feature weights. Moreover, compared with the symmetric weights obtained by other subspace clustering algorithms, the weights of the VSFCM algorithm exhibit significant asymmetry. That is, they assign greater weights to features that contribute more, which is validated on the artificial dataset DATA2 in the experimental section. The experimental results compared with multiple advanced clustering algorithms on the three types of datasets validate that the proposed VSFCM algorithm has the best performance in five indicators. It is demonstrated that the initialization method CDCI is more effective, the feature weight allocation of VSFCM is more consistent with the asymmetry of experimental data, and it can achieve better convergence speed while displaying better clustering efficiency. Full article
(This article belongs to the Special Issue Fuzzy Control Systems: Latest Advances and Prospects)
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