Article
Computer Science, Artificial Intelligence
Sen Liu, Wei Yu, Felix T. S. Chan, Ben Niu
Summary: This article presents a novel hybrid multi-attribute group decision-making approach under IVIFS, incorporating variable weight, correlation coefficient, and TOPSIS. It computes the weighting evaluation matrix based on experts' evaluation in IVIFS and proposes a weighting approach based on correlation coefficient. The method treats attribute weights as a varying vector and uses a variable weighting approach for their acquisition. Ultimately, the integrated assessment value of each alternative is calculated by TOPSIS to determine the most appropriate alternative.
INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS
(2021)
Article
Computer Science, Artificial Intelligence
Meishe Liang, Jusheng Mi, Shaopu Zhang, Chenxia Jin
Summary: Ranking intuitionistic fuzzy numbers is crucial in practical applications of intuitionistic fuzzy sets. Existing measures for ranking these numbers do not comprehensively consider the fuzzy semantics expressed by membership degree, non-membership degree, and hesitancy degree, resulting in counterintuitive ranking results. This paper proposes a novel measure called the ideal measure and a new ranking approach based on geometric representation. The ideal measure is proven to satisfy properties such as weak admissibility, membership degree robustness, non-membership degree robustness, and determinism. A numerical example demonstrates the effectiveness and feasibility of this method, showing that the ideal measure is more effective and simpler than existing methods.
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS
(2023)
Article
Computer Science, Artificial Intelligence
Zhangxu Lin, Jian Lin, Zeshui Xu, Yihong Zhou
Summary: This study proposes a new approach for ranking independent trapezoidal intuitionistic fuzzy numbers based on decision-makers' risk attitudes, and presents a novel similarity measure between two independent trapezoidal intuitionistic fuzzy numbers. It also improves the VIKOR method under the independent trapezoidal intuitionistic fuzzy environment to solve multi-attribute decision-making problems.
INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY & DECISION MAKING
(2023)
Article
Automation & Control Systems
Zhihong Yi, Lijuan Yao, Harish Garg
Summary: This paper introduces trapezoidal Atanassov's intuitionistic fuzzy numbers (TrAIFNs) and its applications. Based on the operation laws defined by strict t-norms and t-conorms, four kinds of power geometric operators are developed, and new ranking and similarity measurement methods for TrAIFNs are proposed. The feasibility and superiority of these methods are demonstrated through a numerical example.
INTERNATIONAL JOURNAL OF FUZZY SYSTEMS
(2023)
Article
Computer Science, Artificial Intelligence
Irfan Deli
Summary: This work investigates multiple attribute decision-making problems with generalized trapezoidal hesitant fuzzy numbers, developing aggregation techniques and decision-making methods for analyzing and discussing decision processes under generalized trapezoidal hesitant fuzzy environments. The proposed approaches based on Bonferroni aggregation operators are applied to multicriteria decision making, with practical examples provided to illustrate the results, followed by a comparative analysis with existing methods.
Article
Computer Science, Interdisciplinary Applications
Jin Ye, Jianming Zhan, Zeshui Xu
Summary: This paper proposes a novel decision-making method based on fuzzy rough sets to transform uncertain data into intuitionistic fuzzy data, establish a new MADM method, and introduce intuitionistic fuzzy weights and global intuitionistic fuzzy thresholds.
COMPUTERS & INDUSTRIAL ENGINEERING
(2021)
Article
Mathematics, Applied
Jeevaraj Selvaraj, Prakash Gatiyala, Sarfaraz Hashemkhani Zolfani
Summary: The use of intuitionistic fuzzy numbers and aggregation operators in decision-making problems effectively addresses uncertainty and incompleteness in information, with trapezoidal intuitionistic fuzzy numbers, Heronian mean operator, and power average operator being commonly used methods. The study also suggests that new aggregation operators can combine the properties of different operators to enhance problem-solving efficiency.
Article
Computer Science, Artificial Intelligence
Aliya Fahmi, Zahida Maqbool, Fazli Amin, Muhammad Aslam
Summary: This paper introduces a trapezoidal fermatean fuzzy-TOPSIS framework for addressing the uncertainties in multi-attribute group decision-making problems in real-life scenes. The framework utilizes trapezoidal fermatean fuzzy sets and an Einstein aggregation operator to model the attitudes of Blockchain knowledge. A case study is conducted to demonstrate the feasibility and effectiveness of the proposed scheme, and sensitivity and comparison analyses are performed to show the robustness and superiority of the method.
Article
Automation & Control Systems
L. Popa
Summary: In this paper, a new ranking function for trapezoidal intuitionistic fuzzy numbers is proposed, based on Robust's ranking index. The function also incorporates a parameter for the attitude of the decision factors. The effectiveness of the method is illustrated through numerical examples and an algorithm for solving fuzzy multi-criteria decision-making problems is proposed.
INTERNATIONAL JOURNAL OF COMPUTERS COMMUNICATIONS & CONTROL
(2023)
Article
Computer Science, Artificial Intelligence
Dharmalingam Marimuthu, G. S. Mahapatra
Summary: This paper focuses on decision-making under uncertainties and proposes a method using complete ranking classification of generalized trapezoidal fuzzy numbers to solve fuzzy multi-criteria decision-making problems. The paper also includes a comparative analysis of existing methods with the proposed method.
Article
Computer Science, Artificial Intelligence
Yan Sun, Xiaojun Zhou, Chunhua Yang, Tingwen Huang
Summary: Multi-attribute decision making (MADM) is widely used in real-world problems, but it imposes a cognitive burden on decision-makers to comprehend the decision-making process and select a satisfactory choice from conflicting alternatives. To solve this problem, a visual analytics approach for MADM (MADM-VA) is proposed. Experimental results show that this approach is efficient and reliable.
INFORMATION FUSION
(2023)
Article
Environmental Sciences
Ju Wu, Yi Liu, Fang Liu, Hao Gong
Summary: This study evaluates land reclamation schemes in mining areas using a multi-attribute group decision-making method. The proposed method provides a simple and effective evaluation by determining expert weights and attribute weights. The practicability of this method is verified through a comparative analysis of land reclamation schemes for four mining areas in Sichuan Province, China.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2022)
Article
Multidisciplinary Sciences
Amir Baklouti
Summary: In multiple-attribute decision-making problems, ranking the alternatives is crucial for making optimal decisions. Intuitionistic fuzzy numbers are an effective tool for dealing with uncertainty and vagueness in these problems. However, current ranking methods for intuitionistic fuzzy numbers fail to consider the probabilistic dominance relationship, resulting in inconsistent and inaccurate rankings. This paper proposes a new ranking method based on the probabilistic dominance relationship and fuzzy algebras, which can handle incomplete and uncertain information and produce consistent and accurate rankings.
Article
Computer Science, Artificial Intelligence
Tapan Senapati, Guiyun Chen, Ronald R. Yager
Summary: This paper describes new intuitionistic fuzzy aggregation operators based on Aczel-Alsina operations, introduces new operations and aggregation operators for IFSs, and demonstrates their properties, followed by the design of new techniques dependent on these operators to solve multiattribute decision making problems.
INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS
(2022)
Article
Mathematics, Applied
Ya Qin, Siti Rahayu Mohd. Hashim, Jumat Sulaiman
Summary: Strengthening the evaluation of teaching satisfaction is crucial in guiding teachers to improve their teaching quality and aiding educational institutions in effective teaching reforms and plans. A new multi-attribute decision-making method combining a new distance measure and an improved TOPSIS method for interval-valued intuitionistic fuzzy sets (IvIFSs) is proposed to enhance the accuracy of evaluation results and improve the discrimination of evaluation information data.
