Applied Soft Computing: Techniques and Applications explores a variety of modern techniques that deal with estimated models and give resolutions to complex real-life issues. Involving the concepts and practices of soft computing in conjunction with other frontier research domains, this book explores a variety of modern applications in soft computing, including bioinspired computing, reconfigurable computing, fuzzy logic, fusion-based learning, intelligent healthcare systems, bioinformatics, data mining, functional approximation, genetic and evolutionary algorithms, hybrid models, machine learning, meta heuristics, neuro fuzzy system, and optimization principles. The book acts as a reference book for AI developers, researchers, and academicians as it addresses the recent technological developments in the field of soft computing.
Soft computing has played a crucial role not only with the theoretical paradigms but is also popular for its pivotal role for designing a large variety of expert systems and artificial intelligent-based applications. Beginning with the basics of soft computing, this book deeply covers 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, meta heuristics, neuro fuzzy system, optimization, randomized searches, and swarm intelligence.
This book is destined for 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.
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Samarjeet Borah, PhD, is a Professor in the Department of Computer Applications, SMIT, Sikkim Manipal University (SMU), Sikkim, India. Dr. Borah handles various academics, research, and administrative activities such as curriculum development, Board of Studies, Doctoral Research Committee, IT Infrastructure Management, etc., at Sikkim Manipal University. He is involved with various funded projects from the All India Council for Technical Education (AICTE) (Govt. of India), Department of Science and Technology–Council of Scientific and Industrial Research (Govt. of India), etc., in the capacity of Principal Investigator/Co-Principal Investigator. He has organized various national and international conferences such as an ISRO-Sponsored Training Programme on Remote Sensing & GIS, NCWBCB-2014, NER-WNLP 2014, IC3-2016, IC3-2018, ICDSM-2019, ICAET-2020, IC3-2020, etc. Dr. Borah is involved with various book volumes and journals of repute for Springer, IEEE, Inderscience, IGI Global, etc., in the capacity of Editor/Guest Editor/Reviewer. He is editor-in-chief of the book series Research Notes on Computing and Communication Sciences, Apple Academic Press, USA.
Ranjit Panigrahi, PhD
, is currently 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 committee for various international journals of Inderscience and Springer Nature. 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.
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.
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