Fr. 178.00

Fuzzy Clustering Algorithms - Symbiotic Relationship Between Mathematics and Similarity Measures.

English · Hardback

Shipping usually within 3 to 5 weeks

Description

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This book bridges theoretical concepts in fuzzy clustering with practical applications. It elucidates the mathematical foundations of fuzzy clustering methods, serving as a much-needed resource in the field. By explicating complex concepts, it will aid researchers, practitioners, and students in the analysis, design, and optimization of algorithms. This valuable resource will contributes to the utilization and enhancement of fuzzy clustering techniques across various domains. The book delves into the mathematical underpinnings, methods, and applications of fuzzy clustering. This book will enable academics, practitioners, and students to grasp the mathematical significance of fuzzy clustering in contemporary data analysis and to explore creative applications. It is an essential volume for data analysis professionals and students alike. Using advanced mathematical methods, it instructs readers on understanding, designing, and applying these algorithms. Its unique blend of theory and practice bridges the mathematical foundation with practical application, empowering readers to effectively analyze large datasets and uncover hidden patterns.

About the author

Dr. Rakesh Kumar
received his Ph.D., M.Phil., and M.Sc in Mathematics from the Department of Mathematics, Lovely Professional University, India. He is currently serving as an Assistant Professor in the Department of Mathematics, Lovely Professional University. He is supervising 4 Ph.D. students and has guided 8 master’s scholars. He authored 25 research articles in international journals of repute and reviewer of many international journals. He is an academic editor and editorial board member of many international journals. His research interests consist of supply chain management, numerical optimization, quality control, multicriteria decision making, and fuzzy optimization, fuzzy clustering, fuzzy neural network, and fuzzy regression models.

Dr. Geeta Arora
earned his Ph.D. degree from
IIT Roorkee
, India in 2011. She is working as a Professor in the Department of Mathematics at Lovely Professional University, Punjab, India. She has over eleven years of teaching experience and published around 50 research papers in both international and national Journals. She has authored 10 book chapters in national and international publications. Also, she has written a book on Quick Calculations in Mathematics and another on Essential Statistics. Her area of research is the development of numerical methods and statistics. She received the research appreciation award in 2017 and 2019 from Lovely Professional University, Punjab, India. She has conducted several workshops on MATLAB and Vedic mathematics for students and faculty members within and outside the university campus. She has supervised 5 students and is currently guiding seven Ph.D. Scholars.

Summary

This book bridges theoretical concepts in fuzzy clustering with practical applications. It elucidates the mathematical foundations of fuzzy clustering methods, serving as a much-needed resource in the field. By explicating complex concepts, it will aid researchers, practitioners, and students in the analysis, design, and optimization of algorithms. This valuable resource will contributes to the utilization and enhancement of fuzzy clustering techniques across various domains. The book delves into the mathematical underpinnings, methods, and applications of fuzzy clustering. This book will enable academics, practitioners, and students to grasp the mathematical significance of fuzzy clustering in contemporary data analysis and to explore creative applications. It is an essential volume for data analysis professionals and students alike. Using advanced mathematical methods, it instructs readers on understanding, designing, and applying these algorithms. Its unique blend of theory and practice bridges the mathematical foundation with practical application, empowering readers to effectively analyze large datasets and uncover hidden patterns.

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