Optimized Computational Intelligence Driven Decision-Making: Theory, Application and Challenges (Industry 5.0 Transformation Applications)

This book covers a wide range of advanced techniques and approaches for designing and implementing computationally intelligent methods in different application domains which is of great use to not only researchers but also academicians and industry experts.

Optimized Computational Intelligence (OCI) is a new, cutting-edge, and multidisciplinary research area that tackles the fundamental problems shared by modern informatics, biologically-inspired computation, software engineering, AI, cybernetics, cognitive science, medical science, systems science, philosophy, linguistics, economics, management science, and life sciences. OCI aims to apply modern computationally intelligent methods to generate optimum outcomes in various application domains. This book presents the latest technologies-driven material to explore optimized various computational intelligence domains.

• includes real-life case studies highlighting different advanced technologies in computational intelligence;
• provides a unique compendium of current and emerging hybrid intelligence paradigms for advanced informatics;
• reflects the diversity, complexity, and depth and breadth of this critical bio-inspired domain;
• offers a guided tour of computational intelligence algorithms, architecture design, and applications of learning in dealing with cognitive informatics challenges;
• presents a variety of intelligent and optimized techniques designed to represent, enhance, and empower multi-disciplinary and multi-institutional data analytics research in intelligent decision-making system dynamics;
• includes architectural models and applications-based augmented solutions for optimized computational intelligence.

Audience

The book will interest a range of engineers and researchers in information technology, computer science, and artificial intelligence working in the interdisciplinary field of computational intelligence.

Hrudaya Kumar Tripathy, PhD, is an associate professor in the School of Computer Engineering, KIIT Deemed to be University, He has more than 20 years of teaching experience and his research interests include neural networks, pattern recognition, software engineering, machine learning, and big data. He has published several books and research papers in various journals and conferences. Tripathy received the 2013 Young IT Professional Award from the Computer Society of India.

Sushruta Mishra, PhD, is an associate professor in the School of Computer Engineering, KIIT Deemed to be University, Odisha, India. He obtained his doctorate in 2017 and his research interests include image processing, machine learning, the Internet of Things, and cognitive computing. He has published 130+ research articles in international journals and conferences.

Minakhi Rout, PhD, is an associate professor in the School of Computer Engineering, KIIT Deemed to be University, Odisha, India. She obtained her PhD in 2015 and her research interests focus on computational finance, data mining, and machine learning. Rout has published 50+ research papers in international journals and conferences.

S. Balamurugan, PhD, is the Director of Research and Development, Intelligent Research Consultancy Services (iRCS), Coimbatore, Tamilnadu, India. He is also Director of the Albert Einstein Engineering and Research Labs (AEER Labs), as well as Vice-Chairman, Renewable Energy Society of India (RESI), India. He has published 45 books, 200+ international journals/ conferences, and 35 patents.

Samaresh Mishra, PhD, is the director of student affairs at KIIT Deemed to be University. He obtained a PhD in computer science from Utkal University. His research areas focus on software testing, machine learning, and cloud computing. He has published 30+ academic papers.