Handbook of Research on Soft Computing and Nature-Inspired Algorithms

Handbook of Research on Soft Computing and Nature-Inspired Algorithms

English | 2017 | ISBN-10: 1522521283 | 627 Pages | PDF, EPUB | 24.73 + 34.41 MB
Soft computing and nature-inspired computing both play a significant role in developing a better understanding to machine learning. When studied together, they can offer new perspectives on the learning process of machines.
The Handbook of Research on Soft Computing and Nature-Inspired Algorithms is an essential source for the latest scholarly research on applications of nature-inspired computing and soft computational systems. Featuring comprehensive coverage on a range of topics and perspectives such as swarm intelligence, speech recognition, and electromagnetic problem solving, this publication is ideally designed for students, researchers, scholars, professionals, and practitioners seeking current research on the advanced workings of intelligence in computing systems.
About the Author
Dr. Shishir K. Shandilya, Ph.D. (Computer Engineering) and M.Tech (CSE), is an excellent academician and active researcher with proven record of teaching and research. He has written five books of international-fame and published over 50 quality research papers in journals & conferences. He has received over 200 international citations on his research papers (Google Scholar). He is actively steering the international conferences and international journals. He is an active member of over 20 international professional bodies. He has achieved excellent results in all the subjects he taught. He is also an excellent programmer and credited various software projects in his account. He is also giving consultancy in IT as Sr. Consultant. He has recently delivered an expert lecture on Opinion Mining at Oxford-United Kingdom
Smita Shandilya (Senior Member-IEEE) is an eminent scholar and energetic researcher with excellent teaching and research skills. She achieved excellent result in all the subjects she has taught till date. She has over 20 quality research papers in international & national journals & conferences to her credits. She has delivered several invited talks in national seminars of high repute. Her research interests are Power System Planning and Smart Micro Grids. She is one of the core members of the research and development section of her Institute. She is also involved in various projects like the establishment of Energy Lab in the Institute (first in any Private Institute in M.P.), Establishment of Training cum Incubator centre in Collaboration with iEnergy.
Kusum Deep is a Professor, with the Department of Mathematics, Indian Institute of Technology Roorkee, India. Born on August 15, 1958, she pursued B.Sc Hons and M.Sc Hons. School from Centre for Advanced Studies, Panjab University, Chandigarh. A M.Phil Gold Medalist, she earned her PhD from IIT Roorkee in 1988. She has nearly 60 research publications in refereed International Journals and more than 52 research papers in International / National Conferences. She has co-authored a book entitled Optimization Techniques by New Age Publishers New Delhi in 2009 with an International edition by New Age Science, UK. Her research interests include Numerical Optimization, Evolutionary Algorithms, Genetic Algorithms, Particle Swarm Optimization, etc.
Atulya K. Nagar is the Foundation Professor of Computer and Mathematical Sciences at Liverpool Hope University and is Head of Department of Computer Science. His teaching expertise is in Applied Analysis, Systems Engineering and Computational Biology. Prof. Nagar earned his PhD in Applied Nonlinear Mathematics from the University of York (UK) in 1996. He holds BSc (Hons.), MSc and MPhil (with distinction) degrees, in Mathematical Sciences, from the MDS University of Ajmer, India. Prior to joining Liverpool Hope University, Prof. Nagar has worked for several years as a Senior Research Scientist, on various EPSRC sponsored research projects, in the department of Mathematical Sciences, and later in the department of Systems Engineering, at Brunel University. In the work at Brunel he has contributed to the development of new techniques based on mathematical control systems theory for modelling and analysis of uncertainty in complex decision making systems.
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