Article
Computer Science, Artificial Intelligence
Ronald R. Yager
Summary: This article introduces the concept and properties of fuzzy measures, providing examples and discussing their application in determining the best course of action in uncertain environments, particularly when payoffs are ordinal rather than numeric.
INFORMATION FUSION
(2022)
Article
Social Sciences, Interdisciplinary
Chunbing Bao, Jie Wan, Dengsheng Wu, Jianping Li
Summary: This paper discusses the aggregation of risk matrices, proposes three methods, and compares them, demonstrating their feasibility and characteristics.
JOURNAL OF RISK RESEARCH
(2021)
Article
Computer Science, Artificial Intelligence
Gurwinder Singh, Amarinder Singh
Summary: This paper proposes an extension of Particle Swarm Optimization to solve fuzzy transportation problems, demonstrating its efficiency through numerical examples and highlighting its superiority over traditional methods in terms of effectiveness and barrier removal.
APPLIED SOFT COMPUTING
(2021)
Article
Physics, Multidisciplinary
Edmundas Kazimieras Zavadskas, Dragisa Stanujkic, Zenonas Turskis, Darjan Karabasevic
Summary: This article presents a new extension of the Integrated Simple Weighted Sum-Product (WISP) method, adapted for intuitionistic numbers, that utilizes intuitionistic fuzzy sets to solve complex decision-making problems.
Article
Water Resources
Vasileios E. Katzourakis, Constantinos Chrysikopoulos
Summary: The migration of nanoparticles in porous media was investigated using a model developed by Katzourakis and Chrysikopoulos (2021). The model simulated the transport of aggregating nanoparticles under different initial conditions. The aggregation process, modeled after the Smoluchowski population balanced equation, was coupled with the conventional advection-dispersion-attachment equation to form a system of equations governing the transport of aggregating nanoparticles. The results highlighted the importance of considering the initial particle concentration and realistic particle diameter distribution.
ADVANCES IN WATER RESOURCES
(2023)
Article
Mathematics, Applied
Talha Midrar, Saifullah Khan, Saleem Abdullah, Thongchai Botmart
Summary: Due to the vagueness and uncertainty in human cognition and judgments, existing fuzzy decision-making approaches lack credibility measures for fuzzy assessment values. This research proposes new procedures for credible fuzzy numbers based on Dombi t-norm and Dombi t-conorm, and develops a series of fuzzy credibility Dombi aggregation operators.
Article
Mathematics, Applied
Rana Muhammad Zulqarnain, Xiao Long Xin, Muhammad Saeed
Summary: Intuitionistic fuzzy hypersoft set is a new technique for expressing insufficient evaluation, uncertainty, and anxiety in decision-making, and can handle uncertain and fuzzy information more effectively. The concepts and properties of correlation coefficient and weighted correlation coefficient are proposed, along with the introduction of TOPSIS technique and aggregation operators based on these coefficients. This method's effectiveness is demonstrated through a case study on decision-making difficulties and a comparative analysis with existing studies.
Article
Operations Research & Management Science
Manuel Arana-Jimenez
Summary: This paper proposes a new method for obtaining fuzzy Pareto solutions of a fully fuzzy multiobjective linear programming problem. By combining triangular fuzzy numbers and variables with fuzzy partial orders and fuzzy arithmetic, algorithms are provided to generate fuzzy Pareto solutions, including compromise fuzzy Pareto solutions, which is a novelty in this field.
RAIRO-OPERATIONS RESEARCH
(2022)
Article
Automation & Control Systems
Chiranjibe Jana, Madhumangal Pal
Summary: This article studies the dynamic hybrid multi-attribute decision making process, proposes new dynamic weighted aggregation operators, and applies grey relational analysis to analyze aggregated data for final ranking.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2021)
Article
Computer Science, Artificial Intelligence
Muhammad Sajjad Ali Khan, Chiranjibe Jana, Muhammad Tahir Khan, Waqas Mahmood, Madhumangal Pal, Wali Khan Mashwani
Summary: This article introduces a new multiattribute group decision-making approach with Linguistic Pythagorean fuzzy numbers (LPFNs). The approach extends the traditional grey relational analysis (GRA) method and introduces a new distance measure and entropy measure for LPFNs. It also provides steps for solving LPFMAGDM problems with incomplete weight information.
INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS
(2022)
Article
Computer Science, Artificial Intelligence
Liangshao Hou, Jieyong Zhou, Qixiang He
Summary: An extension method is proposed to solve fully fuzzy Sylvester matrix equation by transferring the system into interval systems and then extending them into crisp systems. The solutions are not presumed to be triangular-type fuzzy numbers and the validity of the method is demonstrated through examples.
Article
Computer Science, Artificial Intelligence
Shang-Ming Zhou, Francisco Chiclana, Robert John, Jonathan M. Garibaldi, Lin Huo
Summary: This study explores the properties of T1OWA operators when dealing with fuzzy sets as inputs and associated weights, showing that they possess the same properties as Yager's OWA operators. Numerical examples and a case study on diabetes diagnosis validate the effectiveness of these properties in aggregating uncertain information sources and improving integrated diagnosis.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2021)
Article
Mathematics, Applied
Muhammad Qiyas, Muhammad Naeem, Neelam Khan, Lazim Abdullah
Summary: A bipolar complex fuzzy credibility set (BCFCS) is introduced as a new method in computational intelligence and decision-making under uncertainty. The use of bipolar complex fuzzy credibility (BCFC) information is proposed to handle confusing and unreliable situations in everyday life. Aggregation operators are employed to diagnose existing averaging and geometric aggregation operators and evaluate their properties and related results. An algorithm for multiple criteria group decision making is presented using the described operators. A numerical example of Hospital selection is discussed, and a comparative analysis of the suggested operators with existing operators is provided to examine their rationality, efficiency, and applicability.
Article
Computer Science, Artificial Intelligence
Muhammet Gul, M. Fatih Ak
Summary: This paper proposes a modified FMEA model based on spherical fuzzy sets using the IVSF-TOPSIS method to replace traditional RPN calculations, adding parameters such as cost, prevention, and effectiveness. A case study is provided to demonstrate the applicability of the model, showing that the most crucial failure modes are related to factory maintenance and lifting vehicle inspections.
Article
Computer Science, Artificial Intelligence
Shuping Wan, Jiuying Dong
Summary: This article presents a new intuitionistic fuzzy BWM (IFBWM) method for multicriteria decision-making. The article formulates the derivation of optimal IF weights as an IF decision-making problem and constructs mathematical programming models. It also investigates the process of improving the consistency. Several examples are provided to demonstrate the effectiveness of the proposed IFBWM.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2022)
Article
Physics, Multidisciplinary
Ludmila Dymova, Krzysztof Kaczmarek, Pavel Sevastjanov, Joanna Kulawik
Summary: The paper summarizes the experience in solving multiple criteria decision-making problems and focuses on the most frequently used mathematical tools and methodologies in decision-making practice.
Article
Chemistry, Multidisciplinary
Ludmila Dymova, Krzysztof Kaczmarek, Pavel Sevastjanov
Summary: This paper introduces a method for fuzzy multiple-criteria optimization of rolled-steel heat treatment processes, establishing regression dependencies between quality outputs and technological input parameters using statistical methods. Local criteria membership functions are formed based on quality parameters, and a practical methodology for optimizing technological processes is proposed. The efficiency of the optimal heat treatment modes obtained significantly exceeds that of earlier technologies used in the plant.
APPLIED SCIENCES-BASEL
(2021)
Article
Physics, Multidisciplinary
Pavel Sevastjanov, Ludmila Dymova, Krzysztof Kaczmarek
Summary: In this paper, a critical analysis of Neutrosophic, Pythagorean, and other novel fuzzy sets theories is provided, revealing shortcomings and proposing alternative approaches for improvement. The author suggests extending intuitionistic fuzzy sets within the framework of the Dempster-Shafer theory to address the internal problems of Atanassov's intuitionistic fuzzy sets and enhance upon them.
Article
Computer Science, Artificial Intelligence
Ludmila Dymova, Krzysztof Kaczmarek, Pavel Sevastjanov
Summary: The study proposes a new approach to fuzzy portfolio selection based on simple criteria of portfolio risk and return, developing single-period and multi-period models successfully applied to real stock market data. The method optimizes real market decisions and incorporates stock signals into the models, enhancing the realism of the results.
KNOWLEDGE-BASED SYSTEMS
(2021)
Article
Computer Science, Artificial Intelligence
Krzysztof Kaczmarek, Ludmila Dymova, Pavel Sevastjanov
Summary: This paper presents the application of the intuitionistic fuzzy rule-base evidential reasoning (IFRBER) in developing a new optimized automated trading system (ATS) for the Forex market. The IFRBER approach represents intuitionistic fuzzy sets within the framework of the evidence theory, addressing the limitations of the IFS operational laws and improving overall performance. The study demonstrates that the IFRBER approach extracts more useful information for decision making compared to the usual fuzzy rule-base evidential reasoning. Based on the IFRBER approach, a new method for making justified buying and selling decisions is proposed, leading to the development of a highly profitable and low-risk optimized ATS.
APPLIED SOFT COMPUTING
(2022)
Article
Computer Science, Artificial Intelligence
Ludmila Dymova, Krzysztof Kaczmarek, Pavel Sevastjanov
Summary: The paper introduces a new method of rule base evidential reasoning based on interval-valued intuitionistic fuzzy values, focusing on competing fuzzy categories and proposing a new mathematical object called belief interval bounded belief interval (BIBBI) for a more reliable representation of interval-valued intuitionistic fuzzy values.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Computer Science, Artificial Intelligence
Pavel Sevastjanov, Ludmila Dymova, Krzysztof Kaczmarek
Summary: Recently, a useful redefinition of the intuitionistic and interval-valued intuitionistic fuzzy set theories based on the Dempster-Shafer theory of evidence was developed, named the Belief-Plausibility approach. This paper proposes a new approach to compare real, interval and fuzzy-valued intuitionistic fuzzy and BP numbers. The redefinition based on the BP approach allows for the development of new methods for comparison in the framework of the BP approach.
INTERNATIONAL JOURNAL OF APPROXIMATE REASONING
(2023)
Article
Computer Science, Information Systems
Pavel Sevastjanov, Ludmila Dymova, Krzysztof Kaczmarek
Summary: The problems of A-IFS and A-IVIFS theories were analyzed, and a new redefinition based on the Dempster-Shafer theory was developed, introducing a new concept called Belief-Plausibility number (BPN). The approach to processing interval-valued intuitionistic fuzzy objects and their Belief-Plausibility redefinitions allowed for the introduction of a set of useful definitions that were not previously mentioned in the literature. The practical utility of the introduced Belief-Plausibility approach was illustrated through the solution of a real-world multiple criteria problem, showing visible advantages over the A-IFS based approach.
Article
Computer Science, Artificial Intelligence
Ludmila Dymova, Krzysztof Kaczmarek, Pavel Sevastjanov, Lukasz Sulkowski, Krzysztof Przybyszewski
Summary: This study proposes a new approach to extend the application of the TOPSIS technique in the intuitionistic fuzzy environment by redefining the A-IFS theory in the framework of DST. The use of DST mathematical tools helps to avoid limitations of conventional Atanassov's operational laws and improve the quality of aggregating operators.
JOURNAL OF ARTIFICIAL INTELLIGENCE AND SOFT COMPUTING RESEARCH
(2021)
