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Computational Intelligence based Optimization of Manufacturing Process for Sustainable Materials (Computational and Intelligent Systems) - Softcover

 
9781032191102: Computational Intelligence based Optimization of Manufacturing Process for Sustainable Materials (Computational and Intelligent Systems)

Synopsis

The text comprehensively discusses computational models including artificial neural networks, agent-based models, and decision field theory for reliability engineering. It will serve as an ideal reference text for graduate students and academic researchers in the fields of industrial engineering, manufacturing engineering, computer engineering, and materials science.

  • Discusses the development of sustainable materials using metaheuristic approaches.
  • Covers computational models such as agent-based models, ontology, and decision field theory for reliability engineering.
  • Presents swarm intelligence methods such as ant colony optimization, particle swarm optimization, and grey wolf optimization for solving the manufacturing process.
  • Include case studies for industrial optimizations.
  • Explores the use of computational optimization for reliability and maintainability theory.

The text covers swarm intelligence techniques including ant colony optimization, particle swarm optimization, cuckoo search, and genetic algorithms for solving complex industrial problems of the manufacturing industry as well as predicting reliability, maintainability, and availability of several industrial components.

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About the Author

Dr. Deepak Sinwar is an Associate Professor at the Department of Computer and Communication Engineering, Manipal University Jaipur, Jaipur, Rajasthan, India. He received his Ph.D and M.Tech degrees in Computer Science and Engineering in 2016 and 2010 respectively; and B.Tech (with honors) in Information Technology in 2008. On his credit, he has published more than 50 articles in peer reviewed journals, conference proceedings, and book chapters.

He has published three edited books published by Springer, CRC Press, and Scrivener (Wiley). He is currently editing three more books for reputed publishers including CRC Press (Taylor & Francis) and Springer. He has worked as guest editor for a special issue entitled, “Sustainable development in Computational Intelligence and Computer Vision” of “International Journal of Social Ecology and Sustainable Development (IJSESD) – IGI Global. He has published 3 patents and 7 copyrights in the field of computer software. He has supervised 1 Ph.D thesis, 11 M.Tech dissertations and currently supervising 4 Ph.D scholars. He has organized three international conferences viz. ICICV-2020, ICICV-2021 and ICICV-2022 supported by Springer. Dr. Sinwar is a recipient of “Top Researcher of the Year – 2021” by Manipal University Jaipur, India for his research contributions in year 2021. He has organized and attended various workshops during his teaching career. His research interests include Computational Intelligence, Data Mining, Machine Learning, Reliability Theory, Computer Networks and Pattern Recognition. He is an enthusiastic and motivating technocrat with more than 12 years of research and academic experience. He is a life member of Indian Society for Technical Education (India), senior member of IEEE and member of ACM professional society.

Dr. Kamalakanta Muduli, is presently working as Associate Professor in the Department of Mechanical Engineering, Papua New Guinea University of Technology, Lae, Morobe Province, Papua New Guinea. He is also a visiting researcher at University of Derby, UK. He has obtained PhD from School of Mechanical Sciences, IIT Bhubaneswar, Orissa, India. Dr. Muduli has over 16 years of academic experience in Universities in India and Papua New Guinea. Dr. Muduli is a recipient of ERASMUS+ KA107 award provided by European Union. He has published 69 papers in peer reviewed international journals most of which are indexed in Clarivate analytics, Scopus and listed in ABDC and more than 34 papers in National and International Conferences. He has been also guest edited 5 Special Issues in journals and 8 books published by Springer, Taylor and Francis, MDPI, CRC Press, Wiley scrivener and Apple Academic Press. Dr. Muduli also has guided three PhD students. His current research interest includes Materials Science, Manufacturing, Sustainable supply chain management, and Industry4.0 applications in operations and supply chain management. Dr. Muduli is a fellow of Institution of Engineers India. He is also a senior member of Indian Institution of Industrial Engineering and member of ASME.

Prof. V S Dhaka is a seasoned academician with a flair for entrepreneurial spirit. He enjoys a persistent passion for continuous learning for self and students’ growth. He has more than 17 years of experience in the software industry, academics, research, teaching, and training. His continuous diligence in refining Academic Quality, Building Research Acumen, Developing Entrepreneurial Culture, Improving Experiential Learning and Creating Fostering Culture for innovation has facilitated students of Manipal University Jaipur in achieving laurels at various platforms. Further, He has more than 100 publications in journals of great repute in his name and guided 13 research scholars to earn Ph.D. He is also executing DST sponsored research projects, supervising Ph.D. research scholars and many funded student projects so that strong concepts can lead to great professional skills.

Dr. Vijander Singh received his Ph.D. degree from Banasthali University, Banasthali, India, in April 2017, and the M.Tech. degree (Hons.) from Rajasthan Technical University, in 2019. He also qualified NET and GATE examinations, in 2012 and 2018, respectively. He is currently working as a Postdoctoral Fellow at the Cyber-Physical Systems Laboratory, Department of ICT and Natural Sciences, Faculty of Information Technology and Electrical Engineering, Norwegian University of Science and Technology, Norway, and an Associate Professor with the Department of Computer Science and Engineering, Manipal University Jaipur, Jaipur, India. He has published more than 40 journal articles, 15 conference papers, ten book chapters, and two edited books. His research interests include machine learning, deep learning, precision agriculture, and networking. He is handling journals of international repute as a guest editor. He has organized several international conferences, FDPs, and workshops, as core team member of organizing committee.

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Paperback. Condition: new. Paperback. The text comprehensively discusses computational models including artificial neural networks, agent-based models, and decision field theory for reliability engineering. It will serve as an ideal reference text for graduate students and academic researchers in the fields of industrial engineering, manufacturing engineering, computer engineering, and materials science. Discusses the development of sustainable materials using metaheuristic approaches. Covers computational models such as agent-based models, ontology, and decision field theory for reliability engineering. Presents swarm intelligence methods such as ant colony optimization, particle swarm optimization, and grey wolf optimization for solving the manufacturing process. Include case studies for industrial optimizations. Explores the use of computational optimization for reliability and maintainability theory. The text covers swarm intelligence techniques including ant colony optimization, particle swarm optimization, cuckoo search, and genetic algorithms for solving complex industrial problems of the manufacturing industry as well as predicting reliability, maintainability, and availability of several industrial components. The text comprehensively discusses computational models including artificial neural networks, agent-based models, and decision field theory for reliability engineering. It will serve as an ideal reference text for graduate students and academic researchers in the field of industrial engineering Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9781032191102

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