Article
Computer Science, Artificial Intelligence
Zhiqiang Luo, Jun Hu, Qinghua Zhang, Guoyin Wang
Summary: This paper proposes a novel method to induce interval shadowed sets based on a new objective function, which reduces fuzziness loss and improves computing efficiency by determining thresholds and optimizing the algorithm.
INTERNATIONAL JOURNAL OF APPROXIMATE REASONING
(2023)
Article
Computer Science, Artificial Intelligence
Qinghua Zhang, Man Gao, Fan Zhao, Guoyin Wang
Summary: This article proposes the FeGTSS model based on fuzzy entropy loss, analyzes the fuzzy entropy loss of shadowed sets, searches for the optimal game strategy in calculating (alpha, beta) based on the dichotomy algorithm, and extends and discusses the FeGTSS model based on analysis of different data distribution types.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2022)
Article
Computer Science, Information Systems
Stefania Boffa, Andrea Campagner, Davide Ciucci, Yiyu Yao
Summary: This article studies aggregation operators on shadowed sets and explores the relationships between these operators and the corresponding operators on fuzzy sets. The focus is on studying the homomorphism conditions when approximating fuzzy sets into shadowed sets, and proposing classes of fuzzy set operators that correspond to specific shadowed set operators.
INFORMATION SCIENCES
(2022)
Article
Computer Science, Artificial Intelligence
Giovanni Acampora, Roberto Schiattarella, Autilia Vitiello
Summary: This article introduces the first quantum-based fuzzy inference engine that provides exponential acceleration in fuzzy rule execution compared to classical methods, and enables quantum computers to be programmed using fuzzy linguistic rules.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2023)
Article
Computer Science, Artificial Intelligence
Kaihong Guo, Hao Xu
Summary: This paper aims to establish a new mathematical framework for knowledge measure using IVIFSs and apply it to image thresholding, creating a knowledge-driven thresholding methodology. The developed technique shows superior performance in application, marking a new instance for potential areas of this theory in image processing.
APPLIED SOFT COMPUTING
(2021)
Review
Mathematics
Simona Dzitac, Sorin Nadaban
Summary: This paper pays tribute to Professor Ioan Dzitac and his significant contributions in the field of soft computing methods in a fuzzy environment. It also highlights his achievements and gratitude towards his mentor, Lotfi A. Zadeh, and discusses future trends in the field.
Article
Computer Science, Theory & Methods
Tamunokuro Opubo William-West, Musa Adeku Ibrahim
Summary: This paper presents a shadowed set S that interprets and makes decisions with a fuzzy set F using approximation regions and a tri-valued mapping. The principle of uncertainty relocation is used to balance the uncertainty of F in S. A trade-off principle between uncertainty and certainty is proposed to minimize the amount of unclassified data and maximize the number of crisp decisions. The optimum partition threshold for a trade-off three-region shadowed set is determined and generalized to a five-region model S5. The existence and uniqueness of the optimum partition threshold of S5 are investigated, and application examples are outlined.
FUZZY SETS AND SYSTEMS
(2023)
Article
Computer Science, Information Systems
Prashant K. Gupta, Deepak Sharma, Javier Andreu-Perez
Summary: This research demonstrates the similarity between linguistic computational models based on the extension principle and symbolic method, and Yager's generalized CWW framework. It also introduces two novel CWW methodologies based on Intuitionistic fuzzy sets (IFSs) and rough sets for modeling the semantics of linguistic information. The study highlights the drawback of the extension principle in treating linguistic information with equal weights during aggregation.
INFORMATION SCIENCES
(2021)
Article
Computer Science, Artificial Intelligence
Ehsan Adel-Rastkhiz, Mohammad-R. Akbarzadeh-T
Summary: The article proposes an alternative view of interpretability for fuzzy models based on specificity, which effectively deals with the subjectivity inherent in linguistic interpretation. In addition to this semantic improvement, a specificity-based hierarchical fuzzy structure is introduced to handle the complexity of interpretability. This structure employs a two-level hierarchy to localize general rules at the first level and reduce computational burden while still allowing for real-time operation.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2021)
Article
Computer Science, Information Systems
Jilin Yang, Yiyu Yao
Summary: This paper investigates two possible solutions for constructing a shadowed set from an Atanassov intuitionistic fuzzy set, using optimization and Chebyshev distance to determine thresholds. The results are useful for three-way decision.
INFORMATION SCIENCES
(2021)
Article
Computer Science, Artificial Intelligence
Ahmet Sakalli, Tufan Kumbasar, Jerry M. Mendel
Summary: This article presents a new perspective on using GT2 fuzzy sets to design fuzzy logic controllers, analyzing the impact of design parameters (DPs) on controller performance, and proposing methods for adjusting DPs to strike a balance between performance and robustness.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2021)
Article
Computer Science, Artificial Intelligence
Shuyin Xia, Hao Zhang, Wenhua Li, Guoyin Wang, Elisabeth Giem, Zizhong Chen
Summary: Feature reduction is crucial in Big Data analytics, and rough sets are commonly used for attribute reduction. However, existing rough set algorithms have limitations in terms of efficiency and effectiveness. To address these issues, a novel method called granular ball neighborhood rough sets (GBNRS) is proposed, which outperforms the current state-of-the-art method in terms of performance and classification accuracy.
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
(2022)
Article
Computer Science, Artificial Intelligence
Linjie He, Yumin Chen, Keshou Wu
Summary: This article introduces a new fuzzy granular deep convolutional network to address the issues in traditional neural networks by incorporating granulation concept and residual structures. Experimental results demonstrate the network's good generalization performance and effectiveness.
KNOWLEDGE-BASED SYSTEMS
(2022)
Article
Chemistry, Multidisciplinary
Cinthia Peraza, Patricia Ochoa, Oscar Castillo, Patricia Melin
Summary: This article proposes the use of the theory of shadowed type-2 fuzzy sets to address complex control problems and reduce computational costs. By employing two alpha planes in the harmony search algorithm, effective results can be obtained. The simulations demonstrate that including noise improves the system's performance.
APPLIED SCIENCES-BASEL
(2023)
Article
Computer Science, Information Systems
Shifan He, Xiaohong Pan, Yingming Wang
Summary: This paper proposes an extended TODIM method based on shadowed sets to solve large-scale group decision making problems. The method involves constructing a codebook, proposing a new similarity measure, and considering the psychological behavior of decision makers for improved decision efficiency and outcome.
INFORMATION SCIENCES
(2021)
