Soft Computing for Data Analytics, Classification Model, and Control

This book discusses soft computing approaches and their applications in data analytics, classification model, and control. It covers fuzzy logic implementation, rough sets, neutrosophic sets, type-2 fuzzy logic, neural networks, generative adversarial networks, and evolutionary computation. The book is divided into two thematic parts, with the first section focusing on text classification and data analysis and the second section on fuzzy driven optimization methods for control systems. Chapters are written by active researchers and provide insights into the design of hybrid algorithms for these applications.

Format: Paperback / softback
Length: 165 pages
Publication date: 01 February 2023
Publisher: Springer Nature Switzerland AG

This comprehensive book delves into the realm of soft computing approaches, showcasing their invaluable applications in data analytics, classification models, and control systems. It serves as a valuable resource for both researchers and practitioners seeking to harness the power of these innovative techniques.

The book begins by providing a foundational understanding of fuzzy logic implementation, a key component in advanced hybrid fuzzy driven optimization methods. It then explores a wide range of soft computing techniques, including Fuzzy Logic, Rough Sets, Neutrosophic Sets, Type-2 Fuzzy logic, Neural Networks, Generative Adversarial Networks, and Evolutionary Computation. These techniques are applied across diverse domains, such as data analytics, classification models, and engineering control, offering solutions to complex problems.

The book is organized into two thematic parts. The first section focuses on soft computing approaches for text classification and data analysis, while the second section delves into fuzzy driven optimization methods for control systems. Each chapter is authored by experienced researchers who provide comprehensive insights into the theoretical foundations, hypotheses, and practical considerations associated with these algorithms. The chapters also offer practical examples and case studies to illustrate the effectiveness of the discussed techniques in real-world applications.

By presenting a diverse range of soft computing approaches and their practical applications, this book serves as a valuable resource for students, researchers, and professionals in the fields of data analytics, classification modeling, and control systems. It equips readers with the knowledge and tools necessary to leverage the power of soft computing in addressing challenging problems and achieving optimal outcomes.

Weight: 279g
Dimension: 235 x 155 (mm)
ISBN-13: 9783030920289
Edition number: 1st ed. 2022