Article
Computer Science, Information Systems
Meenakshi Kaushal, Harish Garg, Q. M. Danish Lohani
Summary: The paper proposes a novel approach that utilizes Atanassov intuitionistic fuzzy sets (AIFS) to cluster datasets and identify outliers. It introduces a new function called the typicality function for outlier detection and parameter tuning to improve clustering. To optimize the tuning process and reduce time complexity, a global error search approach (k-GESA) is introduced. The paper also presents a new clustering algorithm called Global Intuitionistic Fuzzy Weighted C-Ordered Means (Global-IFWCOM), which improves clustering results using k-GESA. The effectiveness of the proposed approach is evaluated against various C-ordered means algorithms on synthetic datasets with outliers, and compared to the Fuzzy Weighted C-Ordered Means (FWCOM) algorithm on a dataset with noise and outliers.
INFORMATION SCIENCES
(2023)
Article
Physics, Multidisciplinary
Chengli Fan, Qiang Fu, Yafei Song, Yingqi Lu, Wei Li, Xiaowen Zhu
Summary: This article proposes a dynamic multi-time fusion target threat assessment method that effectively improves the accuracy and reliability of target threat assessment in missile defense by introducing new computational models and operators, as well as an improved distance measurement model.
Article
Computer Science, Artificial Intelligence
Harish Garg, Zeeshan Ali, Tahir Mahmood
Summary: This article introduces the concept of complex interval-valued q-rung orthopair fuzzy set (CIVq-ROFS) as a generalization of existing fuzzy set theories, aiming to better express time-periodic problems and two-dimensional information. The article discusses the basic properties of CIVq-ROFSs, as well as introduces averaging aggregation operator (AAO) and geometric aggregation operator (GAO) for operations on CIVq-ROFSs, extending previous operations in various fuzzy set theories. Additionally, the article explores the application of CIVq-ROFS in decision-making methods such as Analytic Hierarchy Process (AHP) and technique for order preference by similarity to ideal solution (TOPSIS) to assess its reliability and efficiency.
Article
Computer Science, Artificial Intelligence
Muhammad Irfan Ali, Jianming Zhan, Muhammad Jabir Khan, Tahir Mahmood, Haider Faizan
Summary: This paper discusses the distribution and relationship of uncertainties in Atanassov intuitionistic fuzzy sets, defines knowledge measures as a function of entropy and uncertainty index with specific properties, and establishes the existence of such measures. It further demonstrates how these knowledge measures are useful in multi-criteria group decision-making problems.
Article
Computer Science, Information Systems
Michal Boczek, LeSheng Jin, Marek Kaluszka
Summary: The study explores the structures and properties of interval-valued fuzzy operators and introduces the concept of interval-valued seminormed fuzzy operator (ISFO). The research reveals related properties of admissible orders and cones, leading to a fundamental structural analysis of ISFO.
INFORMATION SCIENCES
(2021)
Article
Computer Science, Artificial Intelligence
Haojun Fang, Tahir Mahmood, Zeeshan Ali, Shouzhen Zeng, Yun Jin
Summary: This study explores the application of Aczel-Alsina fuzzy operational laws in the theory of complex interval-valued intuitionistic fuzzy (CIVIF) sets, and proposes multiple operators for managing information in this theory. The study also investigates the WASPAS method for CIVIF information and applies it to multi-attribute decision-making. The superiority and dominancy of the proposed methods are demonstrated through sensitivity analysis and graphical representation of the results.
PEERJ COMPUTER SCIENCE
(2023)
Article
Computer Science, Information Systems
Tahir Mahmood, Jabbar Ahmmad, Zeeshan Ali, Miin-Shen Yang
Summary: Due to the complexities of different diseases, accurate medical diagnosis has become a difficult task for experts. Researchers are developing new methods to overcome these difficulties. This article proposes novel techniques to aid experts in accurately diagnosing diseases, including the establishment of confidence-level intuitionistic fuzzy aggregation operators and a medical diagnosis model based on the intuitionistic fuzzy rough model.
Article
Computer Science, Artificial Intelligence
Xinming Shi, Zeeshan Ali, Tahir Mahmood, Peide Liu
Summary: In this study, Aczel-Alsina t-norm and t-conorm are extended to Interval-valued Atanassov intuitionistic fuzzy set (IVA-IFS), and the interval-valued Atanassov intuitionistic fuzzy Aczel-Alsina power averaging (IVA-IFAAPA), interval-valued Atanassov intuitionistic fuzzy Aczel-Alsina power ordered averaging (IVA-IFAAPOA), interval-valued Atanassov intuitionistic fuzzy Aczel-Alsina power geometric (IVA-IFAAPG), and interval-valued Atanassov intuitionistic fuzzy Aczel-Alsina power ordered geometric (IVA-IFAAPOG) operators are proposed. The properties of these operators are discussed, and a multi-attribute decision-making procedure is proposed to process the IVA-IF information. A practical example is used to demonstrate the effectiveness and superiority of the proposed method compared to existing operators.
INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMS
(2023)
Article
Computer Science, Information Systems
Eda Bolturk, Cengiz Kahraman
Summary: The study introduces interval-valued intuitionistic fuzzy PW analysis and circular intuitionistic fuzzy PW analysis to handle the impreciseness in the estimation of PW analysis parameters.
Article
Computer Science, Information Systems
Naijie Chai, Wenliang Zhou, Zhigang Jiang
Summary: The sustainable supplier selection process involves a lot of uncertain information, which cannot be perfectly described by traditional fuzzy sets. Therefore, this study develops a novel fuzzy multi-criteria decision-making approach based on intuitionistic fuzzy sets, interval-valued fuzzy sets, and cumulative prospect theory for selecting the most sustainable supplier.
INFORMATION SCIENCES
(2023)
Article
Chemistry, Multidisciplinary
Abdul Nasir, Naeem Jan, Abdu Gumaei, Sami Ullah Khan, Fahad R. Albogamy
Summary: Technology is advancing rapidly, leading to digitalization of various aspects of life and the emergence of cyberattacks. The study of interval-valued complex intuitionistic fuzzy relations and the use of Hasse diagrams help in analyzing different cybersecurity techniques. By identifying the most beneficial cybersecurity method and comparing different options, the proposed approach can provide insights into the advantages of selected cybersecurity methods.
APPLIED SCIENCES-BASEL
(2021)
Article
Mathematics
Zeeshan Ali, Tahir Mahmood, Miin-Shen Yang
Summary: In this paper, the authors derive the Frank operational laws for CIF information and propose prioritized aggregation operators based on these laws. They also introduce the WASPAS method under the consideration of CIF information and provide numerical examples to compare the proposed operators with existing ones in multi-attribute decision-making procedures, demonstrating the validity and worth of the proposed approaches.
Article
Computer Science, Artificial Intelligence
Saeed Zeraatkar, Fatemeh Afsari
Summary: Imbalanced data classification is a complex issue where traditional classifiers perform poorly due to imbalanced class distribution. This paper proposes a solution involving resampling the data in two phases, oversampling and undersampling, using robust extensions of KNN classifiers based on interval-valued fuzzy and intuitionistic fuzzy sets. The proposed method shows potential in handling both synthetic and real-world data sets with different levels of noise and borderlines.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Mathematics
Muhammad Riaz, Hafiz Muhammad Athar Farid, Weiwei Wang, Dragan Pamucar
Summary: This article introduces the concept of interval-valued linear Diophantine fuzzy set and analyzes its accuracy using Frank operations. It also offers new operations and aggregation operators for interval-valued linear Diophantine fuzzy information. The practicality and viability of these operators are demonstrated through a numerical case study.
Article
Automation & Control Systems
J. Jansi Rani, A. Manivannan, S. Dhanasekar
Summary: Civilization is established through transportation activities worldwide, which in turn plays a crucial role in a country's economic growth. To optimize transportation and maximize profits, it is necessary to minimize transportation costs, which can vary due to unforeseen factors. This study proposes modeling transportation problem cost parameters as interval valued intuitionistic fuzzy numbers to address uncertainties. A new subtraction operation and optimal method are developed for solving transportation problems, and a new ordering for interval valued trapezoidal intuitionistic fuzzy numbers is proposed based on Yager's formula.
INTERNATIONAL JOURNAL OF FUZZY SYSTEMS
(2023)
Article
Computer Science, Theory & Methods
Gleb Beliakov, Francisco Javier Cabrerizo, Enrique Herrera-Viedma, Jian-Zhang Wu
Summary: The theory of capacities provides a powerful formal methodology for addressing criteria dependencies in multiple criteria decision problems. This study focuses on randomly generating capacities for simulation studies and for capacity learning through evolutionary algorithms. The results are supported by extensive numerical evidence and offer a useful tool for large scale simulations.
FUZZY SETS AND SYSTEMS
(2022)
Article
Computer Science, Theory & Methods
Tim Wilkin, Gleb Beliakov
Summary: This article discusses techniques for calculating the mode of compositional data and the challenges it faces in real-world applications, such as computational complexity and oversmoothing.
FUZZY SETS AND SYSTEMS
(2022)
Article
Computer Science, Theory & Methods
Gleb Beliakov, Marek Gagolewski, Simon James
Summary: The use of the Choquet integral allows for effective modeling of interactions and dependencies between data features or criteria in data fusion processes. This paper studies hierarchical aggregation processes that are structurally similar to feed-forward neural networks, simplifying the fitting problem and proposing a fuzzy measure method based on the Mobius representation.
FUZZY SETS AND SYSTEMS
(2022)
Correction
Computer Science, Theory & Methods
Gleb Beliakov, Enrique de Amo, Juan Fernandez-Sanchez, Manuel Ubeda-Flores
Summary: This article corrects the formula for the best-possible upper bound on the set of copulas with a given value of the Spearman's footrule coefficient that was recently published in [1].
FUZZY SETS AND SYSTEMS
(2022)
Article
Computer Science, Theory & Methods
Gleb Beliakov, Dmitriy Divakov
Summary: This paper outlines recent trends in capacity-based aggregation in large universes, discussing the importance of fuzzy measures in modeling input dependencies and exploring the challenges and approaches to reducing the complexity of aggregation.
FUZZY SETS AND SYSTEMS
(2022)
Article
Computer Science, Artificial Intelligence
Gleb Beliakov, Simon James, Anna Kolesarova, Radko Mesiar
Summary: This article formalizes an approach to extended aggregation functions to limit the influence of repeated inputs or regions of high density on the final value. Important definitions and properties are established, and a powerful construction method is proposed with illustrative examples provided throughout.
INFORMATION FUSION
(2021)
Article
Computer Science, Artificial Intelligence
Gleb Beliakov, Simon James
Summary: This paper discusses the importance of measures of diversity, spread and inequality in various fields, introduces the P-D principle and ordered weighted averaging operators, and proposes the Choquet integral as a potential method for defining welfare measures. The concept of buoyancy is extended to fuzzy measures, and the optimization problem of the Choquet integral under linear constraints is explored, providing an efficient linear programming solution for antibuoyant fuzzy measures.
INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS
(2022)
Article
Computer Science, Theory & Methods
Gleb Beliakov, Enrique de Amo, Juan Fernandez-Sanchez, Manuel Ubeda-Flores
Summary: This paper investigates the pointwise best-possible bounds on the set of copulas with a given value of the Spearman's footrule coefficient. It is found that the lower bound is always a copula but the upper bound can be a copula or a proper quasi-copula, with both cases being characterized.
FUZZY SETS AND SYSTEMS
(2022)
Article
Computer Science, Artificial Intelligence
Gleb Beliakov
Summary: This article addresses the challenging problem of random sampling from discrete fuzzy measures. It converts the problem to sampling from an order polytope and efficiently handles it using the Markov chain random walk.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2022)
Article
Computer Science, Information Systems
Gleb Beliakov, Simon James
Summary: This work focuses on solving optimization problems using the Choquet integral as the objective function, which allows for interaction between coalitions of decision variables. Efficient solution approaches are proposed for problems with a large number of variables, leveraging the antibuoyancy property and extending it to general fuzzy measures. Theoretical results are supported by numerical experiments, showing significant performance gains and scalability to a higher number of variables.
INFORMATION SCIENCES
(2021)
Article
Computer Science, Theory & Methods
Gleb Beliakov, Marek Gagolewski, Simon James
Summary: This paper examines the class of antibuoyant fuzzy measures and their application in Choquet integrals. By determining subsets of extreme points, three algorithms for randomly generating fuzzy measures are proposed, which are also applicable to fitting empirical data or solving best approximation problems. The study reveals the potential applications of these methods in social welfare, ecology, and optimization.
FUZZY SETS AND SYSTEMS
(2022)
Article
Computer Science, Artificial Intelligence
Gleb Beliakov, Thang Cao, Vicky Mak-Hau
Summary: This study addresses the problems of mutual dependence in multiple criteria decision-making and multiobjective optimization in the context of land combat vehicle selection for Australian Defence. The criteria dependencies are modeled and formalized using fuzzy measure theory. The main challenge lies in the large number of parameters quantifying all criteria interactions. Strategies such as simplifying model construction, eliciting preferences from numerical simulations and decision makers, and translating preferences into a fuzzy measure learning problem are developed. A mathematical programming problem is formulated and tested to determine fuzzy measure parameters for a relatively large number of decision criteria.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2022)
Article
Automation & Control Systems
Juan Zhao, Tianrui Zong, Yong Xiang, Guang Hua, Xinyu Lei, Longxiang Gao, Gleb Beliakov
Summary: FSMP is a frequency spectrum modification process proposed to defend against collusion attacks, significantly degrading the perceptual quality of colluded files and deterring attackers. The method is orthogonal to traditional anti-collusion methods and can provide double-layer protection.
IEEE TRANSACTIONS ON CYBERNETICS
(2023)
Article
Computer Science, Theory & Methods
Irina Perfilieva, Shokrollah Ziari, Rahele Nuraei, Thi Minh Tam Pham
Summary: The proposed approach uses the F-transform to construct an operational matrix for solving the Volterra integral equation. The transformed form of the equation reduces to a system of linear equations with a triangular matrix, making the numerical method efficient and low computational. The paper provides proofs of convergence, estimation of computational complexity, and compares the results with other methods using test cases.
FUZZY SETS AND SYSTEMS
(2024)
Article
Computer Science, Theory & Methods
Yongliang Yang, Guilong Liu, Qing Li, Choon Ki Ahn
Summary: This paper proposes a novel type of Nussbaum function to handle the feedback control design problem with multiple unknown time-varying control coefficients. By separately compensating the unknown control coefficients and combining with the fixed-time stability theory, the issue of mutual cancellation is resolved and Lyapunov stability analysis becomes feasible. The theoretical discussions and simulation experiments demonstrate the effectiveness of the presented design for continuous-time stochastic nonlinear dynamical systems.
FUZZY SETS AND SYSTEMS
(2024)
Article
Computer Science, Theory & Methods
Yingfang Li, Xingxing He, Dan Meng, Keyun Qin
Summary: This paper presents an improved method for estimating the similarity between LR-type fuzzy numbers and compares it with existing methods. The proposed method overcomes the shortcomings of existing methods by considering the shape of LR-type fuzzy numbers.
FUZZY SETS AND SYSTEMS
(2024)
Article
Computer Science, Theory & Methods
Tong Kang, Leifan Yan, Long Ye, Jun Li
Summary: This note solves an open problem proposed in the paper Kang et al. (2023) [9] by demonstrating the linearity of set-valued pan-integrals based on a fuzzy measure and the operations pair (+, center dot) through the subadditivity of the fuzzy measure. It also provides an example to show the necessity of the subadditivity condition for the linearity of set-valued pan-integrals. Furthermore, it introduces the pan-integral of set-valued functions based on a fuzzy measure and pan-operations pair (circle plus, circle times).
FUZZY SETS AND SYSTEMS
(2024)
Article
Computer Science, Theory & Methods
Marzieh Shamsizadeh, Mohammad Mehdi Zahedi, Mohamad Javad Agheli Goki
Summary: In this paper, we study a new generalization for the notion of fuzzy automata, called hesitant L-fuzzy automaton (HLFA). The mathematics framework for the theory of HLFA is presented. Moreover, the concepts of hesitant L-fuzzy behavior and inverse hesitant L-fuzzy behavior recognized by a type of HLFA are introduced. Additionally, a minimal complete accessible deterministic hesitant L-fuzzy automaton is presented for recognizing any hesitant L-fuzzy language, and an algorithm is proposed to determine the states of the minimal hesitant L-fuzzy automaton along with its time complexity.
FUZZY SETS AND SYSTEMS
(2024)
Article
Computer Science, Theory & Methods
S. O. Mashchenko
Summary: This paper investigates a fuzzy matrix game with fuzzy sets of player strategies and proposes a method to construct a game value using Zadeh's extension principle and the approach to fuzzy matrix games. It is proved that the fuzzy sets of players strategies in a fuzzy matrix game generate a game value in the form of a type-2 fuzzy set on the real line.
FUZZY SETS AND SYSTEMS
(2024)
Article
Computer Science, Theory & Methods
Gustave Bainier, Benoit Marx, Jean-Christophe Ponsart
Summary: The Nonlinear Sector Approach (NLSA) is a method to construct Takagi-Sugeno (T-S) models that precisely represent nonlinear systems with bounded nonlinearities. This paper generalizes the NLSA to polytopic and smooth convex bounding sets, providing new ways to reduce the conservatism of TS representations with interdependent scheduling parameters. Various Linear Matrix Inequalities (LMI) criteria are also provided for stability analysis of these models.
FUZZY SETS AND SYSTEMS
(2024)
Article
Computer Science, Theory & Methods
Mi Zhou, Ya-Jing Zhou, Jian-Bo Yang, Jian Wu
Summary: This study proposes a new dissimilarity measure for basic probability assignments (BPAs) in the Dempster-Shafer evidence structure, considering both distance measure and conflict belief. Comparative analysis demonstrates the applicability and validity of the proposed measure, which is further applied to multi-source data fusion and large-scale group decision making.
FUZZY SETS AND SYSTEMS
(2024)
Article
Computer Science, Theory & Methods
Nicolas Madrid, Manuel Ojeda-Aciego
Summary: This paper continues the research on the properties of the f-indexes of inclusion and contradiction, and specifically demonstrates the relationship between the two concepts through the reformulated Aristotelian square of opposition.
FUZZY SETS AND SYSTEMS
(2024)
Article
Computer Science, Theory & Methods
Hanbiao Yang, Zhongqiang Yang, Taihe Fan, Lin Yang
Summary: This paper discusses the topological structures on fuzzy numbers and their related sets, and investigates the continuity of weighted mean maps with respect to these structures. An application of the results is provided, demonstrating their practical significance.
FUZZY SETS AND SYSTEMS
(2024)
Article
Computer Science, Theory & Methods
Narayan Choudhary, S. P. Tiwari, Shailendra Singh
Summary: This paper studies different compositions of (L-fuzzy) automata using category theory and introduces four different categories for the study. It shows that each category has specific properties and advances the existing categories in the field. The monoidal description of these categories enriches the fuzzy automata theory.
FUZZY SETS AND SYSTEMS
(2024)
Article
Computer Science, Theory & Methods
Lifeng Li, Qinjun Luo
Summary: In this study, we investigate monotone comparative statics under interval uncertainty. We introduce interval-valued supermodular functions and interval-valued quasisupermodular functions with respect to a partial order relation on intervals. Moreover, we derive some sufficient conditions for monotone comparative statics under interval uncertainty. We also apply these results to analyze the monotone comparative statics of interval games with strategic complements.
FUZZY SETS AND SYSTEMS
(2024)