Swarm Intelligence - Pandey, Jitendra Kumar

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Résumé :
Swarm intelligence is one of the fastest-growing sub-fields of artificial intelligence and soft computing. This field includes multiple optimization algorithms to solve NP-hard problems for which conventional methods are not effective. It inspires researchers in engineering sciences to learn theories from nature and incorporate them....

Biographie:

Abhishek Sharma received the bachelor's degree in Electronics and Communication Engineering from ITM-Gwalior, India, in 2012, and the master's degree in Robotics Engineering from the University of Petroleum and Energy Studies (UPES), Dehradun, India, in 2014. He was a Senior Research Fellow in a DST funded project under the Technology Systems Development Scheme. He was an Assistant Professor with the Department of Electronics and Instrumentation, UPES. He is working as a research scientist in research and development department, UPES. His research interests include embedded system, optimization, swarm intelligence and robotics

Abhinav Sharma received his B. Tech from H. N. B. Garhwal University, Srinagar, India, in 2009 and the M. Tech from Govind Ballabh Pant University of Agriculture and Technology, Pantnagar, India, in 2011. He did his Ph. D. from Govind Ballabh Pant University of Agriculture and Technology, Pantnagar, India, in 2016. He is working as an Assistant Professor (Senior Scale) in the Department of Electrical and Electronics Engineering in University of Petroleum and Energy Studies, Dehradun. His field of interest includes adaptive array signal processing, Artificial Intelligence, and Machine Learning, Optimization Techniques and smart antenna

Jitendra Kumar Pandey was born in Bakeware, Uttar Pradesh, India. He received his BSc (Biochemistry, 1996) and MSc (Organic Chemistry, 1998), from the University of Kanpur, India. He has received is Ph.D. degree from National Chemical Laboratory Pune, in the area of polymer science and his thesis title was Degradability of Polymer Composites from Renewable Resources. He worked as business development manager-International Business SRL Ranbaxy Ltd., Andheri-East, India. He is working as a Professor and Dean School of Basic & Applied Science, Adamas University, West Bengal, India. His area of expertise is Polymer nanocomposites, Bio-composites, Natural Nano-particles, Water treatment.

Mangey Ram received the Ph.D. degree major in Mathematics and minor in Computer Science from G. B. Pant University of Agriculture and Technology, Pantnagar, India. He has been a Faculty Member for around twelve years and has taught several core courses in pure and applied mathematics at undergraduate, postgraduate, and doctorate levels. He is currently a Research Professor at Graphic Era (Deemed to be University), Dehradun, India. Before joining the Graphic Era, he was a Deputy Manager (Probationary Officer) with Syndicate Bank for a short period. He is Editor-in-Chief of the International Journal of Mathematical, Engineering and Management Sciences, Book Series Editor with Elsevier, CRC Press-A Taylor, and Frances Group, De Gruyter Publisher Germany, River Publisher, USA and the Guest Editor & Member of the editorial board of various journals. He has published 225 plus research publications in IEEE, Taylor & Francis, Springer, Elsevier, Emerald, World Scientific, and many other national and international journals and conferences. His fields of research are reliability theory and applied mathematics. Dr. Ram is a Senior Member of the IEEE, life member of Operational Research Society of India, Society for Reliability Engineering, Quality and Operations Management in India, Indian Society of Industrial and Applied Mathematics, He has been a member of the organizing committee of several international and national conferences, seminars, and workshops. He has been conferred with the Young Scientist Award by the Uttarakhand State Council for Science and Technology, Dehradun, in 2009. He has been awarded the Best Faculty Award in 2011...

Sommaire:
1. Swarm Intelligence: Review, Perspective and Challenges. 2. Theory to Practice in PSO. 3. Survey on New Swarm Intelligence Algorithms. 4. Engineering Applications of Swarm Intelligence. 5. Swarm Intelligence Applications in Machine Learning....