Article
Computer Science, Artificial Intelligence
Peide Liu, Weiqiao Liu
Summary: The paper introduces the dual generalized weighted Bonferroni mean operator and the dual generalized weighted Bonferroni geometric mean operator for 2DULVs, aiming to handle multi-attribute decision making problems. By combining different operators, the approach demonstrates validity and superiority through illustrative examples and comparisons with other methods.
ARTIFICIAL INTELLIGENCE REVIEW
(2021)
Article
Multidisciplinary Sciences
Miin-Shen Yang, Zeeshan Ali, Tahir Mahmood
Summary: This paper introduces complex q-rung orthopair uncertain linguistic sets (CQROULSs) and related operators for handling multi-attribute decision making (MADM) issues, with properties such as idempotency, boundedness, and commutativity. The proposed method is innovative and important for MADM problems.
Article
Computer Science, Artificial Intelligence
Tahir Mahmood, Muhammad Ahsen, Zeeshan Ali
Summary: Picture hesitant fuzzy sets are a valuable tool for expressing uncertain information, surpassing intuitionistic fuzzy sets and hesitant fuzzy sets in certain aspects. The proposed picture hesitant fuzzy mean operators offer a new method for dealing with decision-making in uncertain environments, with demonstrated effectiveness and superiority in practical examples.
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
Automation & Control Systems
Sayanta Chakraborty, Apu Kumar Saha
Summary: The proposed Multi-Criteria Group Decision Making (MCGDM) method based on Fermatean fuzzy set has been applied to determine the optimal Health Care Waste (HCW) treatment technologies (TT) for sustainable environmental development. The method considers six TTs as alternatives and nine criteria for evaluation. The proposed technique shows competitiveness and stability through an empirical case study of district hospitals in Tripura, India.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2023)
Article
Computer Science, Artificial Intelligence
K. Janani, S. S. Mohanrasu, Chee Peng Lim, Balachandran Manavalan, R. Rakkiyappan
Summary: Feature selection is necessary due to the rapid increase in digital technology, which allows for the generation of large quantities of high-dimensional data in a short amount of time. Ensemble feature selection has emerged as a potential approach to data mining, with the advantage of identifying multiple optimal features.
APPLIED SOFT COMPUTING
(2023)
Article
Mathematics, Applied
Tahir Mahmood, Ubaid Ur Rehman, Zeeshan Ali, Muhammad Aslam
Summary: In a professional environment, decision-making techniques are necessary to handle complex situations. This paper introduces a decision-making technique developed using interpreted aggregation operators, highlighting their advantages and characteristics. The paper also explores the application of derived operators and presents experimental results evaluating the reliability and practicality of the proposed theory.
Article
Multidisciplinary Sciences
Yuan Xu, Shifeng Liu, Jun Wang
Summary: This study focuses on the application of interval-valued q-rung orthopair fuzzy sets in multiple-attribute group decision-making problems, proposing a new definition of interval-valued q-rung orthopair uncertain linguistic sets and a model framework. Through comparative analysis, the performance and advantages of the new method are demonstrated.
Article
Computer Science, Information Systems
Swati Rani Hait, Bapi Dutta, Debashree Guha, Debjani Chakraborty
Summary: The study focuses on extending the application of the Bonferroni mean operator by generalizing the relationship patterns among data entities. An improved version of the BM operator, called the f BM G operator, is proposed, which portrays unconventional associations among data entities through graphical patterns. The f BM G operator embeds the interactional information depicted through graphs into its processing system to capture precise interconnections among entities. A generalized variation of the f BM G operator is also proposed to meet the mandatory prerequisites of decision systems, and a detailed analysis and numerical example are provided to demonstrate their efficiency.
INFORMATION SCIENCES
(2022)
Article
Mathematics
Lu Zhang, Yabin Shao, Ning Wang
Summary: This paper introduces interaction partitioned Bonferroni mean operators under the dual hesitant q-rung orthopair fuzzy environment. The proposed operators are based on the laws of q-rung orthopair fuzzy interaction, partitioned Bonferroni mean, and dual hesitant q-rung orthopair fuzzy sets. Several aggregation operators are presented, including the weighted interaction partitioned Bonferroni mean operator and the interaction partitioned geometric Bonferroni mean operator for dual hesitant q-rung orthopair fuzzy numbers. The properties and special cases of these operators are analyzed, and a multicriteria group decision-making method is proposed. An example is provided to demonstrate the superiority and feasibility of the proposed method compared to existing methods.
JOURNAL OF MATHEMATICS
(2023)
Article
Mathematics
Wei Yang, Yongfeng Pang
Summary: In this paper, T-spherical fuzzy Bonferroni mean operators are developed by extending the Bonferroni mean and Dombi mean to a T-Spherical fuzzy environment, to deal with complicated decision problems. Several T-spherical fuzzy Bonferroni mean operators are proposed, and their properties are studied. A new decision making method based on these operators is also proposed.
Article
Engineering, Multidisciplinary
Tahir Mahmood, Zeeshan Ali, Dulyawit Prangchumpol, Thammarat Panityakul
Summary: Neutrosophic sets have a greater power than fuzzy sets, with the ability to account for true, false, or indeterminate components. However, simultaneous variations can make neutrosophic sets unsuitable for certain circumstances. By combining multi-valued neutrosophic uncertain linguistic sets and complex fuzzy sets, the concept of multi-valued complex neutrosophic uncertain linguistic sets is developed to address these issues.
CMES-COMPUTER MODELING IN ENGINEERING & SCIENCES
(2022)
Article
Computer Science, Artificial Intelligence
Yibo Wang, Xiuqin Ma, Hongwu Qin, Huanling Sun, Weiyi Wei
Summary: This research presents the definition of hesitant Fermatean fuzzy Bonferroni mean operator (HFFBM) and derives the hesitant Fermatean fuzzy Einstein Bonferroni mean operator (HFFEBM) using basic operations of hesitant Fermatean fuzzy sets in Einstein t-norms. It also develops the hesitant Fermatean fuzzy weighted Bonferroni mean (HFFWBM) operator and the hesitant Fermatean fuzzy Einstein weighted Bonferroni mean operator (HFFEWBM), considering the influence of weights on decision-making outcomes. Moreover, a new multi-attribute decision-making (MADM) approach based on HFFWBM and HFFEWBM operator is provided and applied to a depression diagnostic evaluation with satisfactory results.
COMPLEX & INTELLIGENT SYSTEMS
(2023)
Article
Multidisciplinary Sciences
Juxiang Wang, Xiangyu Zhou, Si Li, Jianwei Hu
Summary: This paper proposes new operational methods for PLTSs based on Dombi T-conorm and T-norm, aiming to solve the problem of losing subjective preference information for decision-makers. The PLWDBMPA operator is used to fuse the evaluation information of decision-makers, while online comments from social media platforms are used to understand the public's attitude. A novel multi-attribute group decision-making method based on TODIM method is proposed, and its superiority is verified through case studies and comparisons with other methods.
Article
Multidisciplinary Sciences
Xiaopeng Yang, Tahir Mahmood, Jabbar Ahmmad
Summary: This article introduces the concept of picture fuzzy soft Bonferroni mean aggregation operators and weighted picture fuzzy soft Bonferroni mean aggregation operators, and provides some basic properties of these aggregation operators. As cancer is one of the most rapidly increasing diseases globally, it is difficult to determine which type of cancer is increasing rapidly due to the different kinds of cancer diseases. Therefore, the application of fuzzy ideas in medical diagnosis problems is proposed to reduce the difficulty in the medical field. Additionally, an algorithm and descriptive example are presented to validate the initiated work, and a comparative analysis is conducted to demonstrate the efficiency and superiority of the introduced work over other existing theories.
