Computational Intelligence: Theories, Applications and Future Directions - Volume I
Description
This book presents selected proceedings of ICCI-2017, discussing theories, applications and future directions in the field of computational intelligence (CI). ICCI-2017 brought together international researchers presenting innovative work on self-adaptive systems and methods. This volume covers the current state of the field and explores new, open research directions. The book serves as a guide for readers working to develop and validate real-time problems and related applications using computational intelligence. It focuses on systems that deal with raw data intelligently, generate qualitative information that improves decision-making, and behave as smart systems, making it a valuable resource for researchers and professionals alike.
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Dr. Nishchal K. Verma (SM'13) is an Associate Professor at the Department of Electrical Engineering, Indian Institute of Technology Kanpur, India. He obtained his PhD in Electrical Engineering from the Indian Institute of Technology Delhi. He worked as a Postdoctoral Research Fellow at the Center for Integrative and Translational Genomics, University of Tennessee, Memphis, TN, USA and Postdoctoral Research Associate at the Department of Computer Science, Louisiana Tech University, Ruston, LA, USA. He was awarded the Devendra Shukla Young Faculty Research Fellowship by the Indian Institute of Technology Kanpur, India (2013-16) and Indo-Canadian SFTIG Award of CAD$6000 for Shastri Faculty Training and Internationalization Program (2017-18). His research interests include cognitive science, big data analysis, bioinformatics, intelligent data mining algorithms and applications, computer vision and image processing, brain computer/machine interface, machine intelligence, intelligent informatics, smart grids, intelligent fault diagnosis systems, prognosis and health management, soft-computing in modelling and control, Internet of Things/cyber-physical systems, intelligent agents and their applications, fuzzy logic and controllers, deep learning of neural and fuzzy networks, machine learning algorithms, and computational intelligence. He has authored more than 200 research papers and is an IETE Fellow. He is currently an Editor of the IETE Technical Review Journal, an Associate Editor of the IEEE Computational Intelligence Magazine, and of the Transactions of the Institute of Measurement and Control, U.K. and an Editorial Board Member for several journals and conferences.
Dr. A. K. Ghosh is a Professor at the Department of Aerospace Engineering, Indian Institute of Technology Kanpur, India. He obtained his PhD in Aerospace from the Indian Institute of Technology Kanpur, India. His areas of expertise are in system identification through flight tests using conventional and neural network based methods, design of aircrafts and airborne projectiles, supercavitation, and unmanned aerial systems. He has authored more than 100 research papers.