This book includes best-selected, high-quality research papers presented at Second International Conference on Biologically Inspired Techniques in Many Criteria Decision Making (BITMDM 2021) organized by Department of Information & Communication Technology, Fakir Mohan University, Balasore, Odisha, India, during December 20-21, 2021. This proceeding presents the recent advances in techniques which are biologically inspired and their usage in the field of many criteria decision making. The topics covered are biologically inspired algorithms, nature-inspired algorithms, multi-criteria optimization, multi-criteria decision making, data mining, big-data analysis, cloud computing, IOT, machine learning and soft computing, smart technologies, crypt-analysis, cognitive informatics, computational intelligence, artificial intelligence and machine learning, data management exploration and mining, computational intelligence, and signal and image processing.

Presents research works in the field of many criteria decision making Gather the outcomes of the BITMDM 2021, held in Odisha, India Offers a reference guide for researchers and practitioners in academia and industry

Autorentext

Satchidananda Dehuri is working as Professor in the Department of Information and Communication Technology, Fakir Mohan University, Balasore, Odisha, India, since 2013. He received his M.Tech. and Ph.D. degrees in Computer Science from Utkal University, Vani Vihar, Odisha, in 2001 and 2006, respectively. He visited as BOYSCAST Fellow to the Soft Computing Laboratory, Yonsei University, Seoul, South Korea, under the BOYSCAST Fellowship Program of DST, Govt. of India, in 2008. In 2010, he received Young Scientist Award in Engineering and Technology for the year 2008 from Odisha Vigyan Academy, Department of Science and Technology, Govt. of Odisha. His research interests include evolutionary computation, neural networks, pattern recognition, and data mining. He has already published more than 200 research papers in reputed journals and referred conferences and has published five text books for undergraduate and post-graduate students and edited more than ten books of contemporary relevance. Under his direct supervision, 17 Ph.D. scholars have been successfully awarded. His h-index (Google Scholar) is more than 25. Bhabani Shankar Prasad Mishra born in Talcher, Odisha, India, in 1981. He received the B.Tech. in Computer Science and Engineering from Biju Pattanaik Technical University, Odisha in 2003, M.Tech. degree in Computer Science and Engineering from the KIIT University, in 2005, Ph.D. degree in Computer Science from F. M. University, Balasore, Odisha, India, in 2011, and Post-Doc in 2013 from Soft Computing Laboratory, Yonsei University, South Korea. Currently he is working as Associate Professor at School of Computer Engineering, KIIT University, Bhubaneswar, Odisha, India. His research interest includes pattern reorganization, data mining, soft computing, big data, and machine learning. He has published more than 80 research articles in reputed journal and conferences and has edited more than five books of current importance. Under his guidance, 2 Ph.D. scholars are already been awarded. Dr. Mishra was the recipient of the Gold Medal and Silver Medal during his M.Tech. for the best Post-Graduate in the university. He is Member of different technical bodies ISTE, CSI, and IET. His h-index (Google Scholar) is 14. Dr. Pradeep Kumar Mallick is currently working Senior Associate Professor in the School of Computer Engineering , Kalinga Institute of Industrial technology (KIIT) Deemed to be University, Odisha, India. He has also served as Professor and Head Department of Computer Science and Engineering , Vignana Bharathi Institute of Technology, Hyderabad . He has completed his Post-Doctoral Fellow (PDF) from Kongju National University South Korea, Ph.D. from Siksha Ó' Anusandhan University, M. Tech. (CSE) from Biju Patnaik University of Technology (BPUT), and MCA from Fakir Mohan University Balasore, India. Besides academics, he is also involved various administrative activities, Member of Board of Studies to C.V.Ramman Global University Bhubaneswar, Member of Doctoral Research Evaluation Committee, Admission Committee, etc. His area of research includes Data Mining, Image Processing, Soft Computing, and Machine Learning. Now he is Editorial Member of Korean Convergence Society for SMB .He has published 13 edited books, 1 text book, 2 international patent, and more than 100 research papers in national and international journals and conference proceedings in his credit. Sung-Bae Cho received the Ph.D. degree in computer science from KAIST (Korea Advanced Institute of Science and Technology), Taejeon, Korea, in 1993. He was Invited Researcher of Human Information Processing Research Laboratories at Advanced Telecommunications Research (ATR) Institute, Kyoto, Japan, from 1993 to 1995, and Visiting Scholar at University of New South Wales, Canberra, Australia in 1998. He was also Visiting Professor at University of British Columbia, Vancouver, Canada from 2005 to 2006, and at King Mongkut's University of Technology Thonburi, Bangkok, Thailand in 2013. Since 1995, he has been Professor in the Department of Computer Science, Yonsei University, Seoul, Korea. His research interests include hybrid intelligent systems, soft computing, evolutionary computation, neural networks, pattern recognition, intelligent man-machine interfaces, and games. He has published over 300 journal papers and over 750 conference papers.

Inhalt
Cloud-based Smart Grids: Opportunities and Challenges.- A Resource Aware Load Balancing Strategy for Real-Time, Cross-Vertical IoT Applications.- An Elitist Artificial electric field algorithm - based Artificial Neural Network for Financial Time Series Forecasting.- COVID 19 Severty Predctons: An Analysis Usng Correlaton Measures.- Antenna Array Optimization For Side Lobe Level: A Brief Review.- Accuracy Analysis for Predicting Heart Attacks Based on Various Machine Learning Algorithms.- Link Recommendation for Social Inuence Maximization.- Performance Analysis of State-of-the art Classifiers and Stack Ensemble Model for Liver Disease Diagnosis.- CryptedWe: An end-to-encryption with fake news detection messaging system.- Enabling Data Security in Electronic Voting System using Blockchain.- Prediction of Used Car Prices Using Machine Learning.- Complexity Classification of Object-oriented Projects Based on Class Model Information Using Quasi-opposition Rao Algorithm Based Neural Networks.- Mood Based Movie Recommendation System.