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Computationally Intelligent Systems and their Applications (eBook)

Autor: Jagdish Chand (Hrsg.) Bansal
CHF 201.00
ISBN: 978-981-1604-07-2
Einband: PDF
Verfügbarkeit: Download, sofort verfügbar (Link per E-Mail)
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This book covers all core technologies like neural networks, fuzzy systems, and evolutionary computation and their applications in the systems. Computationally intelligent system is a new concept for advanced information processing. The objective of this system is to realize a new approach for analyzing and creating flexible information processing of sensing, learning, recognizing, and action taking. Computational intelligent is a part of artificial intelligence (AI) which includes the study of versatile components to empower or encourage savvy practices in intricate and evolving situations. The computationally intelligent system highly relies on numerical information supplied by manufacturers unlike AI.

Autor Bansal, Jagdish Chand (Hrsg.) / Paprzycki, Marcin (Hrsg.) / Bianchini, Monica (Hrsg.) / Das, Sanjoy (Hrsg.)
Verlag Springer Nature Singapore
Einband PDF
Erscheinungsjahr 2021
Seitenangabe 164 S.
Ausgabekennzeichen Englisch
Abbildungen XII, 164 p. 60 illus., 49 illus. in color.
Auflage 1st ed. 2021

Über den Autor Jagdish Chand (Hrsg.) Bansal

Dr. Jagdish Chand Bansal is an Associate Professor at South Asian University New Delhi and Visiting Faculty at Maths and Computer Science, Liverpool Hope University UK. Dr. Bansal obtained his Ph.D. in Mathematics from IIT Roorkee. Before joining SAU New Delhi he worked as an Assistant Professor at ABV- Indian Institute of Information Technology and Management Gwalior and BITS Pilani. His Primary area of interest is Swarm Intelligence and Nature Inspired Optimization Techniques. Recently, he proposed a fission-fusion social structure based optimization algorithm, Spider Monkey Optimization (SMO), which is being applied to various problems in the engineering domain. He has published more than 70 research papers in various international journals/conferences. He is the Section Editor (editor in chief) of the journal MethodsX published by Elsevier. He is the series editor of the book series Algorithms for Intelligent Systems (AIS) and Studies in Autonomic, Data-driven and Industrial Computing (SADIC) and Innovations in Sustainable Technologies and Computing (ISTC) published by Springer. He is also the Associate Editor of Engineering Applications of Artificial Intelligence (EAAI) and ARRAY published by Elsevier. He is the general secretary of the Soft Computing Research Society (SCRS). He has also received Gold Medal at UG and PG levels. Harish Sharma is an associate professor in Department of Computer Science & Engineering at Rajasthan Technical University, Kota. He has worked at Vardhaman Mahaveer Open University, Kota, and Government Engineering College, Jhalawar. He received his B.Tech. and M.Tech. degrees in Computer Engg. from Govt. Engineering College, Kota, and Rajasthan Technical University, Kota, in 2003 and 2009, respectively. He obtained his Ph.D. from ABV-Indian Institute of Information Technology and Management, Gwalior, India. He is the secretary and one of the founder members of Soft Computing Research Society of India. He is a lifetime memberof Cryptology Research Society of India, ISI, Kolkata. He is an associate editor of "International Journal of Swarm Intelligence (IJSI)" published by Inderscience. He has also edited special issues of the many reputed journals like "Memetic Computing", "Journal of Experimental and Theoretical Artificial Intelligence", "Evolutionary Intelligence", etc. His primary area of interest is nature-inspired optimization techniques. He has contributed in more than 105 papers published in various international journals and conferences.  Dr. Antorweep Chakravorty is an associate professor at the University of Stavanger. His current research and development work is in the field of applied blockchains, big data, large-scale machine learning, and data privacy. He has an interest in real-world problems, especially development of privacy-enabled data-driven services in smart energy, health care, and smart city domains. Antorweep completed his Ph.D. in 2015 with a thesis on privacy-preserving big data analytics at the University of Stavanger, Norway. Along with having a background in applied research in data-driven solutions, he is also involved in mentoring, teaching, and supervision.

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