This book presents the outcome of two-day 2nd International e-Conference on Sustainable and Innovative Solutions for Current Challenges in Engineering and Technology (ICSISCET 2020) held at Madhav Institute of Technology & Science (MITS), Gwalior, India, from December 18-19, 2020. The book extensively covers recent research in artificial intelligence (AI) that knit together nature-inspired algorithms, evolutionary computing, fuzzy systems, computational intelligence, machine learning, deep learning, etc., which is very useful while dealing with real problems due to their model-free structure, learning ability, and flexible approach. These techniques mimic human thinking and decision-making abilities to produce systems that are intelligent, efficient, cost-effective, and fast. The book provides a friendly and informative treatment of the topics which makes this book an ideal reference for both beginners and experienced researchers.

Autorentext
Dr. Hari Mohan Dubey is Associate Professor in the Department of Electrical Engineering, MITS, Gwalior (India). He received his M.E. degree in Electrical Engineering from MITS, Gwalior, in 2002, and Ph.D. degree in power systems from Rajiv Gandhi Proudyogiki Vishwavidyalaya, Bhopal, India, in 2017. His areas of research include the study of computational intelligence algorithms and their applications to electrical engineering, particularly, renewable integration, distributed generation, power system planning, operation, and control. He has more than 18 years of teaching and research experience. He has published more than 70 research papers published in various reputed international journals/conferences. He is a member of professional bodies like IEEE (USA), IE (India), IETE (India), and ISTE (India).  He is also actively associated with various prestigious international journals as a reviewer. Dr. Manjaree Pandit is currently Dean (Academics) & Professor in the Department of Electrical Engineering, MITS, Gwalior, India. She has completed her graduation and postgraduation from Maulana Azad National Institute of Technology, Bhopal, India, and doctorate from Jiwaji University, Gwalior, India. She has a teaching and research experience of more than 34 years. Her research areas are AI, machine intelligence, evolutionary computation, and electrical power system operation and optimization with renewable energy resources. She is an author and a recognized reviewer for many international publications. She has received national awards twice from ISTE, India, and a research award from UGC, India. Dr. Pandit has received the 'Top Peer Reviewer' award from Publons, Clarivate Analytics for being in the top 1% of reviewers in Engineering for the year 20172018 & 20182019, and also in cross-field for the year 20182019. She has completed 09 centrally funded research projects. She is a senior member of IEEE, USA, and Fellow of Institution of Electronics & Telecommunication Engineers, and Institution of Engineers (India). Dr. Pandit has organized many sponsored technical events like national/international conferences, seminars, workshops, and short-term training programmes. She has published more than 150 research papers in peer-reviewed international journals & conference proceedings and has authored 22 book chapters.  Dr. Laxmi Srivastava received her B.E. and Ph.D. in Electrical Engineering from the University of Roorkee (presently IIT Roorkee) India and M.Tech. in Electrical Engineering from IIT, Kanpur. She joined the Department of Electrical Engineering, Madhav Institute of Technology & Science, Gwalior, in 1984, and is currently working as Professor and Head of this department. She has a teaching and research experience of more than 36 years and has completed more than 12 sponsored research & development projects. She is the recipient of the prestigious Khosla Research award from the University of Roorkee, India (Now IIT, Roorkee). She has been on the review panel of prestigious international journals for the last 20 years. Her research is motivated by ANN, fuzzy logic and evolutionary computing-based techniques for power system security assessment, optimization, control, distributed generation FACTS controllers, and power quality. She is a co-author of two book chapters and has published around 160 papers in peer-reviewed international journals and conference proceedings, which are quite well cited. Dr. Bijaya Ketan Panigrahi is Professor in the Department of Electrical Engineering at the Indian Institute of Technology Delhi. He received his M.Tech. degree in Electrical Engineering from University College of Engineering, Burla, Sambalpur, India, in 1995, and Ph.D. degree from Sambalpur University in 2004. His primary research areas include power quality, flexible alternating current transmission system (FACTS) devices, power system protection, artificial intelligence (AI) applications to power systems, and nature-inspired computing. He is actively working on numerous projects for industry and government. He is a member of various professional societies, including the IEEE (USA). He is serving as a chief editor to the International Journal of Power and Energy Conversion and also associated with many international journals of IEEE, IET, and Elsevier, in different capacities. He has more than 28 years of teaching and research experience. He is a renowned researcher in the field of evolutionary computing and has authored more than 600 research papers published in various reputed international journals and conference proceedings.  His publications are highly cited among the research community in overall disciplines of engineering and science and also have 3 patents in his credits. He is the reci...

Inhalt
Control of On-Board Electric Vehicle Charger.- NSGA III based Time-Cost-Environmental Impact Trade-Off Optimization model for Construction Projects.- Wideband Microstrip Stepped Two-Way Power Divider for 3G/4G Applications.- Simulated Annealing Based Time-Cost Trade-Off Model For Construction Projects.- AHP and NSGA II based Time-Cost-Quality Trade-Off Optimization model for Construction Projects.- A Wavelet Based Segmentation Technique For Medical Images.