Emerging Fuzzy Intelligent Systems for Smart Healthcare Management: Applications of Disc q-Rung Orthopair Fuzzy Sets presents comprehensive methodological frameworks and the latest empirical research findings concerning disc q-rung orthopair fuzzy operators, with a specific focus on their applications in smart technologies for healthcare management. The book solves a crucial problem by offering readers an invaluable opportunity to conduct a comparative analysis, contrasting the proposed methods with their existing knowledge base. Disc q-Rung Orthopair sets, being the generalization of q-Rung Orthopair fuzzy sets, which are, in turn, the generalization of Pythagorean fuzzy sets, extend the capabilities of handling uncertainty beyond conventional fuzzy sets.
The authors strive to narrow the knowledge gap by clarifying the practical applications of disc q-rung orthopair fuzzy logic. In addition, it explores an enhanced version of q-Rung Orthopair Fuzzy Sets, specifically focusing on Disc q-Rung Orthopair Fuzzy Sets, introducing various types of operators. These operators play a crucial role in solving decision-making and optimization problems. A notable contribution is the development of a hybrid operator, termed as the Disc q-Rung Orthopair Fuzzy Hybrid Weighted Averaging/Geometric (D-qROFHWA/G) operator.
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Dr. Shahzaib Ashraf received the B.S. degree in mathematics from the University of Sargodha, the M.S. degree in (fuzzy) mathematics from International Islamic University, Islamabad, and the Ph.D. degree from Abdul Wali Khan University, Mardan, Pakistan. He is an Assistant Professor in Mathematics at Khawaja Fareed University of Engineering and Information Technology, Rahim Yar Khan, Pakistan. He also served the Bacha Khan University, Charsadda, Pakistan, as an Assistant Professor. He has published 100 research articles with more than 3000 citations. He currently supervises four M.S. and four Ph.D. theses and has supervised four M.S. theses. Dr. Ashraf has published in high impact journals, including International Journal of Intelligent Systems, Soft Computing, and International Journal of Fuzzy Systems. Dr. Ashraf’s specialization is in fuzzy mathematics, spherical fuzzy sets, fuzzy decision support systems, computational intelligence, and soft computing.
Dr. Witold Pedrycz (IEEE Fellow, 1998) is Professor and Canada Research Chair (CRC) in computational intelligence in the Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Canada. In 2012 he was elected a fellow of the Royal Society of Canada. His main research directions involve computational intelligence, fuzzy modeling and granular computing, knowledge discovery and data science, pattern recognition, data science, knowledge-based neural networks, and control engineering. He is also an author of 18 research monographs and edited volumes covering various aspects of computational intelligence, data mining, and software engineering. Dr. Pedrycz is vigorously involved in editorial activities. He is the editor-in-chief of Information Sciences, editor-in-chief of WIREs Data Mining and Knowledge Discovery, and co-editor-in-chief of International Journal of Granular Computing, and Journal of Data Information and Management. He serves on the advisory board of IEEE Transactions on Fuzzy Systems.
Despite the versatility of fuzzy logic across various domains, there remains a gap in understanding, among those, unfamiliar with disc q-Rung orthopair fuzzy operators, particularly in how they are applied in real-life specifically in healthcare management. Emerging Fuzzy Intelligent Systems for Smart Healthcare Management presents comprehensive methodological frameworks and the latest empirical research findings concerning disc q-rung orthopair fuzzy operators, with a specific focus on their applications in smart technologies for healthcare management. The authors strive to narrow the knowledge gap by clarifying the practical applications of disc q-rung orthopair fuzzy logic. The book solves a crucial problem by offering readers an invaluable opportunity to conduct a comparative analysis, contrasting the proposed methods with their existing knowledge base. Disc q-Rung Orthopair sets, being the generalization of q-Rung Orthopair fuzzy sets which in turn being the generalization of Pythagorean fuzzy sets, extend the capabilities of handling uncertainty beyond conventional fuzzy sets. This book explores an enhanced version of q-Rung Orthopair Fuzzy Sets, specifically focusing on Disc q-Rung Orthopair Fuzzy Sets, introducing various types of operators. These operators play a crucial role in solving decision-making and optimization problems. A notable contribution is the development of a hybrid operator, termed as the Disc q-Rung Orthopair Fuzzy Hybrid Weighted Averaging/Geometric (D-qROFHWA/G) operator. The D-qROFHWA/D-qROFHWG operators are applied to address multiple-attribute decision-making (MADM) problems in healthcare management. The authors present comprehensive methodological frameworks and the latest empirical research findings concerning disc q-rung orthopair fuzzy operators, offering insights and support from both practitioners and academia, and providing a cutting-edge exploration of disc q-rung orthopair fuzzy operators and their real-world implementations.
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