26 Best Books on Soft Computing

“Ordinal Optimization: Soft Optimization for Hard Problems” Book Review: In this book, the challenges of optimizing complex systems through simulation models are thoroughly explained. The book begins by introducing the concept of optimization and then discusses the fundamentals of ordinal optimization. It explores various aspects, such as comparing selection rules, vector ordinal optimization, constrained ordinal optimization, and memory-limited strategy optimization. The book discusses additional extensions of the ordinal optimization methodology and presents real-world application examples. To enhance understanding, each chapter concludes with a concise summary.

“Soft Computing: New Trends and Applications ( Advanced Textbooks in Control and Signal Processing)” Book Review: This book provides an explanation of cellular neural networks and explores their applications in handling complex systems. It extensively covers topics such as fuzzy logic, fundamental operators, fuzzy algorithms, fuzzy control, multilayer perceptron, radial basis function, and evolution-type optimization algorithms. The book discusses the analysis of complex dynamic systems and the utilization of neuro-fuzzy networks.

“Soft Computing for Control of Non-Linear Dynamical Systems (Studies in Fuzziness and Computing)” Book Review: This book offers valuable insights into the modeling, simulation, and control of nonlinear dynamical systems. It is divided into two main parts: soft computing and fractal theory. The soft computing section discusses topics such as fuzzy logic, neural networks, and genetic algorithms. On the other hand, the fractal theory section explores mathematical tools that aid in understanding the geometrical complexity observed in natural objects.

“Fuzzy Information and Engineering 2010:Vol 1(Advances in Intelligent and Soft Computing)” Book Review: This book comprises the proceedings of the fifth annual conference on fuzzy information and engineering. It is organized into five sections, each focusing on a specific theme. In total, the book includes 89 papers, providing a coverage of the field. The first section discusses the mathematical theory of fuzzy systems, featuring 15 papers. The second section explores topics of fuzzy logic, systems, and control, presenting 15 papers. The third section is dedicated to fuzzy optimization and decision making, focusing on 24 papers. The fourth section covers fuzzy information, identification, and clustering with 17 papers. Lastly, the fifth section highlights fuzzy engineering applications and soft computing methods, featuring 18 papers.

“Fifty Years of Fuzzy Logic and its Applications (Studies in Fuzziness and Soft Computing)” Book Review: This book provides an exploration of the successful applications of fuzzy sets in artificial intelligence, control theory, inference, and reasoning. It discusses various topics including fuzzy logic, clustering, data mining, and software testing, shedding light on their relevance and practical implications.

“Computational Intelligence for Big Data Analysis (Adaption, Learning and Optimization)” Book Review: This book is divided into three parts. The first part explains the basic theories of analyzing big data. The second part focuses on the structure and setup for analyzing big data. The third part explores the connection between big data analysis and cloud computing. Each chapter concludes with a summary. This book combines the fields of big data analysis, cloud computing, and scientific computing, showcasing their applications and benefits.

“Computer-based Modelling and Optimization in Transportation (Advances in Intelligent Systems and Computing)” Book Review: This book explores various topics including decision-making, decision support, energy and environmental impacts, urban network design, optimization and simulation, traffic modeling, control and network traffic management, and transportation planning. It is a compilation of research conducted by members of the EURO working group on transportation. The book addresses important aspects such as mobility, accessibility, travel behavior, and vehicle routing, providing an overview of the subject matter.

“SOFT COMPUTING :FUNDAMENTALS AND APPLICATIONS” Book Review: This book serves as an introduction to soft computing, a family of computational techniques that includes genetic algorithms, fuzzy logic, and more. It explores the need for non-optimization tools such as genetic algorithms and discusses the principles of traditional optimization. The book provides a thorough explanation of the working cycle and mechanisms of genetic algorithms. It discusses other optimization techniques like simulated annealing and particle swarm optimization. The book also covers combined techniques, including GA-FL, GA-NN, NN-FL, and GA-GL-NN, highlighting their applications and benefits. Algorithms are presented throughout the book, accompanied by solved numerical examples for better understanding.

“Soft Computing and Intelligent Systems Design: Theory, Tools and Applications” Book Review: This book combines mathematical techniques of symbolic logic with programming languages like Prolog and LISP to explore the field of artificial intelligence. It examines how soft computing tools have revolutionized the development of real-world intelligent systems. The book focuses on the analysis of control and intelligent systems design, utilizing various soft computing techniques. It discusses different applications, including industrial contexts. To enhance understanding, the book includes a range of materials such as worked examples, problems, and case studies.

“Soft Computing Applications and Intelligent Systems” Book Review: This book comprises 25 revised full papers carefully chosen from a pool of 110 submissions. These papers were originally presented at the Second International Multi Conference on Artificial Intelligence Technology in August 2013. The selected papers discusses the analysis of various issues related to state-of-the-art research, development, implementation, and applications. The conference primarily emphasizes pattern recognition, data mining, optimization, knowledge technology, and industrial computing.

“Soft Computing Advances and Applications” Book Review: This book provides an exploration of soft computing principles, advancements, and applications. It is specifically designed for undergraduate students studying computer science and information technology. The book covers topics such as fuzzy logic, neurocomputing, and probabilistic reasoning, offering a concise introduction to the fundamental concepts and focuses on both theoretical developments and practical applications.

“Soft Computing and Its Applications, Volume Two: Fuzzy Reasoning and Fuzzy Control: Volume 2” Book Review: This book provides an exploration of the advanced features and hybrid methodologies of soft computing. It is specifically designed for undergraduate and postgraduate students in the fields of electrical, control, electronic and communication, computer science, and information science engineering. Bridging the gap between theory and practice, the book covers topics such as cognitive maps, complex-valued fuzzy sets, and fuzzy logic. It also discusses quantum fuzzy sets, quantum fuzzy logic, rough sets, and hybrid methods. The book discusses existing applications and offers insights into the future scope of work in the field of soft computing.

“Soft Computing Applications (Advances in Intelligent and Soft Computing)” Book Review: This book explores the diverse applications of soft computing in defining flexible systems. It focuses on various fields of application, including image processing, control systems, asset allocation, medicine, and more. The book also addresses topics such as time series forecasting, qualitative modeling, support for design, reliability analysis, and diagnosis. The book is divided into three sections: fuzzy systems, neural networks, and genetic and evolutionary algorithms.

“Soft Computing and Its Application” Book Review: This is a comprehensive book that introduces readers to the field of soft computing and its practical applications. Written by GATE ACADEMY PUBLICATION, this book covers various topics related to soft computing, including fuzzy logic, neural networks, genetic algorithms, and swarm intelligence. The chapters provide clear explanations of the underlying principles and algorithms of each technique, along with examples of real-world applications. Whether you are a student or a professional, this book will enhance your understanding of soft computing and equip you with the knowledge to apply these techniques in solving complex problems.

“Soft Computing Applications in Sensor Networks” Book Review: This book offers an introduction to the fundamental concepts of soft computing with a focus on their practical applications in sensor networks. It focuses on the diverse range of soft computing techniques employed in real-life sensor network applications. The book includes dedicated chapters that address key aspects of sensor networking, such as channel access, routing, coverage, localization, lifetime maximization, and target tracking. These topics are explored through the lens of emerging soft computing applications, providing readers with valuable insights and problem-solving approaches in the field of sensor networking.

“Soft Computing Applications for Database Technologies: Techniques and Issues” Book Review: This book discusses the emerging field of soft computing, which leverages data to address imprecision and uncertainty. It explores a range of methodologies, including fuzzy sets, neural networks, genetic algorithms, Bayesian belief networks, and rough sets. Through extensive research and case studies, the book provides in-depth insights into the applications and techniques of soft computing.

“Soft Computing Applications for Renewable Energy and Energy Efficiency” Book Review: This book explores the latest advancements in computational intelligence and fuzzy logic in addressing environmental challenges. It is specifically designed for students of project engineering and provides an overview of current advancements and future trends in environmental sustainability. The book covers the principles of soft computing and can serve as a valuable reference for researchers, engineers, and practitioners working in the field of energy science.

“Feature Extraction: Foundations and Applications (Studies in Fuzziness and Soft Computing)” Book Review: This is a comprehensive book that explores the fundamental concepts and practical applications of feature extraction. Written by Isabelle Guyon and Steve Gunn, this book delves into the techniques and methodologies used to extract meaningful information from raw data. The chapters cover various topics, including feature selection, feature transformation, dimensionality reduction, and pattern recognition. The authors provide clear explanations of the algorithms and methods involved, accompanied by real-world examples and case studies. Whether you are a student or a researcher in the field of data analysis, this book will enhance your understanding of feature extraction and its importance in various domains.

“Soft Methods in Probability, Statistics and Data Analysis (Advances in Intelligent and Soft Computing)” Book Review: This book is specifically designed for postgraduate students of software engineering, while also serving as a valuable resource for industry professionals seeking to automate tasks. It provides a discussion on mathematical statistics and classical probability theory, discussing the challenges posed by imprecise requirements and vague data. The book explores the incorporation of fuzzy sets and rough sets to enhance classical probability theory, and further examines possibility theory and the theory of belief functions. Richly illustrated with figures and supported by numerous numerical examples, the book also includes practical case studies to reinforce the concepts covered.

“Incomplete Information: Rough Set Analysis (Studies in Fuzziness and Soft Computing)” Book Review: This book is specifically written for postgraduate students of computer engineering, while also serving as a valuable reference for working professionals. It explores the theory of rough sets, a promising methodology for dealing with issues related to imprecise and incomplete data. The book extensively covers the concept of Rough Set Analysis (RSA) and its fundamental principles, providing a detailed understanding of its application. It establishes the connection between the incompleteness of information and the notions of similarity and indiscernibility. The book includes thorough theorem proofs to support the presented concepts and is complemented by practical case studies that help simplify the understanding of the material.

“Deep Fusion of Computational and Symbolic Processing (Studies in Fuzziness and Soft Computing)” Book Review: This book is designed for postgraduate students of computer engineering, while also serving as a valuable reference for working professionals. It discusses the limitations associated with symbolic processing and explores topics such as grounding problems, neural networks, and fuzzy logic. It provides an examination of statistical methods. The book discusses the recent advancements in computational processing and intelligent systems, shedding light on emerging trends in the field. It includes various theorem proofs to support the presented concepts and is enriched with practical case studies that aid in simplifying complex ideas.

“Relational Methods for Computer Science Applications (Studies in Fuzziness and Soft Computing)” Book Review: This book is specifically written for postgraduate students studying computer engineering, but it can also serve as a useful reference for professionals in the field. It explores the origins of relational theories and their applications in various areas. The book covers topics such as databases, computational linguistics, and dependency theory. It also delves into fuzzy relations, handling uncertainty, and the semantics of programming languages. The book includes theorem proofs to support the concepts discussed and provides practical case studies to make the ideas more understandable and relatable.

“Granular, Soft and Fuzzy Approaches for Intelligent Systems: Dedicated to Professor Ronald R. Yager (Studies in Fuzziness and Soft Computing)” Book Review: This book is specifically designed for intelligent systems, providing in-depth information on various aspects of numbers, including data analysis, decision making, and control. It covers topics such as the theory of possibility, Dempster-Shafer theory, and reasoning theory. The book also explores the techniques of application contexts, granular computing, soft computing, and fuzzy logic. It offers constructive research on human cognition, as well as decision making and problem-solving processes.