Hybrid Soft Computing Techniques for Machine Learning and Optimization

ISBN 13: 9798369368688
Published by IGI Global, 2025
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Soft computing approaches, such as fuzzy logic, neural networks, and genetic algorithms, can be integrated into the realms of data analysis and decision making. They can be applied to tackle complex data analysis tasks and support decision-making processes in various domains, including healthcare, finance, manufacturing, and transportation. By extracting meaningful patterns, soft computing techniques may increase the effectiveness and efficiency in handling large datasets. In this way, they may be useful for facilitating decision making in uncertain and dynamic environments. Hybrid Soft Computing Techniques for Machine Learning and Optimization bridges the gap between theoretical knowledge and practical applications in soft computing and data analysis. It explores advancements and innovations in industries where data-driven decision making is crucial. Covering topics such as learning, biomedical signal processing, and entity behaviors, this book is an excellent resource for computer scientists, engineers, practitioners, healthcare professionals, finance professionals, manufacturers, transportation specialists, professionals, researchers scholars, academicians, and more.

About the Authors: Nikhil Kumar Marriwala holds a Post-doc, PhD, M-Tech and B-Tech., in Engineering & Technology and currently serves as an Assistant Professor in the Department of Electronics and Communication Engineering at the University Institute of Engineering and Technology, Kurukshetra University, Kurukshetra. He earned his Postdoc from Amity University, Dubai and PhD from the National Institute of Technology (NIT), Kurukshetra, specializing in Electronics and Communication Engineering. His academic journey includes a post-graduation (M-Tech) in Electronics and Communication Engineering from the Institute of Advanced Studies in Education (IASE) University, along with a B-Tech in Electronics and Instrumentation from MMEC, Mullana, Kurukshetra University, Kurukshetra. With over 21 years of teaching experience at both graduate and postgraduate levels, Dr. Marriwala has significantly contributed to the academic field. As a mentor, he has supervised the successful completion of One PhD student and more than 33 M-Tech dissertations. Also he currently guides 2 students pursuing PhDs. Additionally, he has authored over 10 books with prestigious publishers like Pearson and Wiley, published over 35 papers in reputed international journals, and presented 30 papers in international/national conferences. Dr. Marriwala holds 8 patents, including 2 Indian patents and 6 international patents, showcasing his innovative research contributions. His involvement in academic leadership roles is extensive, having chaired special sessions at over 22 international/national conferences and delivered keynote addresses at 9 international conferences. Furthermore, he has organized multiple international and national conferences, demonstrating his organizational prowess. Dr. Marriwala is also deeply engaged in fostering academic collaborations and knowledge dissemination. He has delivered over 70 invited talks/guest lectures at leading universities and colleges across India. Moreover, he holds additional responsibilities as the Training and Placement Officer at UIET, Kurukshetra University, Kurukshetra, and serves as the Single Point of Contact (SPOC) for various academic initiatives, including the SWAYAM NPTEL Local Chapter and Infosys campus connect program. He is the editor of more than 07 book proceedings with Springer and guest editor for the special session in Journal Measurement and Sensors, Elsevier. He is also the reviewer for many reputed journals. His contributions to academia have been widely recognized, with awards such as the NPTEL Enthusiasts Award and the “Career Guru of the Month” award. Dr. Marriwala has also been acknowledged by Elsevier for his contribution to open science and research addressing the United Nations Sustainable Development Goals. Dr. Marriwala's research interests span across various domains, including Wireless Communications, Software Defined Radios, Cognitive Radios, Soft Computing, Wireless Sensor Networks, Fuzzy System Design, Advanced Microprocessors, Internet of Things, Augmented Reality, Virtual Reality, and Blockchain. His dedication to academia, innovative research, and leadership in the field make Dr. Nikhil Kumar Marriwala a distinguished figure in the realm of Engineering and Technology.

Shruti Jain has received PhD degree from Jaypee University of Information Technology, Waknaghat, Solan. She has a teaching experience of around 13 years and before joining JUIT, she worked as Assistant Professor in Haryana Engineering College, Jagadhari, Ambala College of Engineering, Ambala. She has specialization in Biomedical Signal Processing, Computer- Aided design of FPGA and VLSI circuits, combinatorial optimization. She has published more than 50 papers in reputed journals and 30 papers in International conferences. She is a senior member of IEEE, life member of Biomedical Engineering Society of India and member of IAENG. She is currently working as Associate Professor in the Department of Electronics and Communication Engineering, JUIT Waknaghat.

Vinod Kumar Shukla is currently working with Amity University, Dubai, U.A.E., as Associate Professor and Head of Academics for the Engineering Architecture and Interior Design department. He has more than 15 years of experience. He has completed his PhD in “Semantic Web and Ontology” and is an active member of IEEE. He has appeared in the prestigious Stanford's list, USA of top 2% of scientists for in 2022. He has authored 100+ research publications in journals, book chapters and Conferences, and have 500+ plus Scopus citations. He has edited books in the field of Data Science, Artificial Intelligence, Blockchain, Industry 4.0 and Healthcare, and People Analytics. He is the recipient of various awards such as the “Global Academic Excellence Award- 2021”, “Faculty Achievement Award” under the category of research publication in continuous two years 2021, 2022, “Best Paper Award” in the International Conference on Machine Intelligence and Data Science Application- 2020”. His research area includes cyber security, the Internet of Things, and Blockchain. Currently, he is working on the books and exploring the transition of technologies and their possible impact from Industry 4.0 to Industry 5.0.

Dinesh Kumar completed B.Tech. from IIT Madras and Ph.D. from IIT Delhi and is Professor at RMIT University, Melbourne, Australia. He is a Fellow of Australasian Institute of Digital Health. He has published over 400 papers, authored 8 books, and is on a range of Australian and international committees for Biomedical Engineering. His passion is for affordable diagnostics and making a difference for his students. His work has been cited over 8400 times, and he has also had multiple successes with technology translation. He is Member of Therapeutics Goods Administration (TGA), Ministry of Health (Australia) for medical devices. He is also on the editorial boards for IEEE Transactions of Neural Systems and Rehabilitation Engineering and Biomedical Signals and Controls. He has been Chair of large number of conferences and given over 50 keynotes speeches.

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Title: Hybrid Soft Computing Techniques for Machine...
Publisher: IGI Global
Publication Date: 2025
Binding: Soft cover
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Paperback. Condition: new. Paperback. Soft computing approaches, such as fuzzy logic, neural networks, and genetic algorithms, can be integrated into the realms of data analysis and decision making. They can be applied to tackle complex data analysis tasks and support decision-making processes in various domains, including healthcare, finance, manufacturing, and transportation. By extracting meaningful patterns, soft computing techniques may increase the effectiveness and efficiency in handling large datasets. In this way, they may be useful for facilitating decision making in uncertain and dynamic environments. Hybrid Soft Computing Techniques for Machine Learning and Optimization bridges the gap between theoretical knowledge and practical applications in soft computing and data analysis. It explores advancements and innovations in industries where data-driven decision making is crucial. Covering topics such as learning, biomedical signal processing, and entity behaviors, this book is an excellent resource for computer scientists, engineers, practitioners, healthcare professionals, finance professionals, manufacturers, transportation specialists, professionals, researchers scholars, academicians, and more. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9798369368688

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Paperback. Condition: new. Paperback. Soft computing approaches, such as fuzzy logic, neural networks, and genetic algorithms, can be integrated into the realms of data analysis and decision making. They can be applied to tackle complex data analysis tasks and support decision-making processes in various domains, including healthcare, finance, manufacturing, and transportation. By extracting meaningful patterns, soft computing techniques may increase the effectiveness and efficiency in handling large datasets. In this way, they may be useful for facilitating decision making in uncertain and dynamic environments. Hybrid Soft Computing Techniques for Machine Learning and Optimization bridges the gap between theoretical knowledge and practical applications in soft computing and data analysis. It explores advancements and innovations in industries where data-driven decision making is crucial. Covering topics such as learning, biomedical signal processing, and entity behaviors, this book is an excellent resource for computer scientists, engineers, practitioners, healthcare professionals, finance professionals, manufacturers, transportation specialists, professionals, researchers scholars, academicians, and more. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9798369368688

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