Applied Soft Computing (PDF)
This new volume explores a variety of modern techniques that deal with estimated models and give resolutions to complex real-life issues. Soft computing has played a crucial role not only with theoretical paradigms but is also popular for its pivotal...
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This new volume explores a variety of modern techniques that deal with estimated models and give resolutions to complex real-life issues. Soft computing has played a crucial role not only with theoretical paradigms but is also popular for its pivotal role for designing a large variety of expert systems and artificial intelligence-based applications.
Involving the concepts and practices of soft computing in conjunction with other frontier research domains, this book begins with the basics and goes on to explore a variety of modern applications of soft computing in areas such as approximate reasoning, artificial neural networks, Bayesian networks, big data analytics, bioinformatics, cloud computing, control systems, data mining, functional approximation, fuzzy logic, genetic and evolutionary algorithms, hybrid models, machine learning, metaheuristics, neuro fuzzy system, optimization, randomized searches, and swarm intelligence.
This book will be helpful to a wide range of readers who wish to learn applications of soft computing approaches. It will be useful for academicians, researchers, students, and machine learning experts who use soft computing techniques and algorithms to develop cutting-edge artificial intelligence-based applications.
Samarjeet Borah, PhD, is Professor and Head of the Department of Computer Applications, SMIT, Sikkim Manipal University, Sikkim, India. Dr. Borah has carried out various funded projects from AICTE (GoI), DST-CSRI (GoI), etc. He has organized various workshops and conferences at national and international levels. Dr. Borah is involved with various book volumes and journals. He is the editor-in-chief of the book series Research Notes on Computing and Communication Sciences, published by Apple Academic Press. His areas of research are data mining, data science, and machine learning.
Ranjit Panigrahi, PhD, is Assistant Professor in the Department of Computer Applications at Sikkim Manipal University (SMU), Sikkim, India. His research interests are machine learning, pattern recognition, and wireless sensor networks. Dr. Panigrahi is actively involved in various national and international conferences of repute. He serves as a member of technical review committees for various international journals. He received his MTech in Computer Sciences and Engineering from Sikkim Manipal Institute of Technology and his PhD in Computer Applications from Sikkim Manipal University, India.
- 2022, 1. Auflage, 286 Seiten, Englisch
- Herausgegeben: Samarjeet Borah, Ranjit Panigrahi
- Verlag: Taylor & Francis
- ISBN-10: 1000406636
- ISBN-13: 9781000406634
- Erscheinungsdatum: 02.02.2022
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- Dateiformat: PDF
- Größe: 23 MB
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