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Nature-Inspired Optimization Algorithms for Cyber-Physical Systems (Advances in Computer and Electrical Engineering) - Softcover

 
9798369368350: Nature-Inspired Optimization Algorithms for Cyber-Physical Systems (Advances in Computer and Electrical Engineering)

Synopsis

Cyber-physical systems (CPS) integrate computation, communication, control, and physical elements to achieve shared goals with minimal human intervention, encompassing smart technologies such as cities, cloud computing, and smart grids. As CPS components expand, generating vast amounts of data, they face challenges in areas like resource management, security, computation offloading, and automation, demanding advanced techniques beyond traditional algorithms. Nature-inspired optimization algorithms, drawing on natural phenomena, offer scalable and adaptable solutions for these complex issues, making them essential for addressing CPS challenges efficiently and enhancing their role in our daily lives. Nature-Inspired Optimization Algorithms for Cyber-Physical Systems provides relevant theoretical frameworks and the latest empirical research findings in the area. It explores the nature-inspired optimization algorithms intended to boost the performance of CPS. Covering topics such as ant colony optimization, data analysis, and smart cities, this book is an excellent resource for teaching staff, researchers, academicians, graduate and postgraduate students, and more.

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About the Authors

Mohammad Sajid is an assistant professor in the Department of Computer Science at Aligarh Muslim University, India. He has completed PhD (2016), M. Tech (2012) and MCA (2010) from the School of Computer and Systems Sciences, Jawaharlal Nehru University (JNU), New Delhi. His research interests include Evolutionary and Swarm Intelligence Algorithms, Machine Learning, Combinatorial Optimization Problems, Cloud Computing, Applications of Scheduling and Routing, and Intelligent Transportation Systems. He was awarded a research Startup Grant (INR 10 lakhs) from UGC-BSR (2017), India. He has published many research papers in international conferences and journals of repute (including IEEE, ACM, Elsevier, Springer, Wiley, Taylor & Francis, IGI Global, etc.). He has also published five edited books in CRC Press, Springer (LNNS), and IGI Global. He reviews papers for several reputed international journals (including ACM, IEEE, Taylor and Francis, Elsevier, Springer, Wiley, etc.).

Dr. Mohammad Shahid is an Assistant Professor of Computer Science & Application in the Department of Commerce, A.M.U. Aligarh. He has completed his Ph.D. and M. Tech. from School of Computer and Systems Sciences, Jawaharlal Nehru University (JNU), New Delhi. He earned his M.C.A. from A.M.U. Aligarh. He has published 21 research papers with the publisher of international repute (including Elsevier, Inderscience, Online Wiley, Taylor & Francis, Emerald Insight, IGI Global etc.) and 15 book chapters in springer edited books. Also, he has published 15 research papers in the proceedings of online peer-reviewed International conferences indexed in Scopus. He is awarded with research startup grant (10 lakhs) from UGC-BSR (2017), India. one major research project (6 lakhs) from ICSSR, India, is sanctioned in 2020 under his principal investigation. He is reviewer of the journals from the publishers of international repute (such as Elsevier, Springer, etc.). He is also member of IEEE.

Maria A. Lapina , Candidate of Sciences (Physics and Mathematics), Deputy Director for Research, Associate Professor at the Department of Information Security of Automated Systems, Institute of Digital Development, North Caucasus Federal University, Stavropol, Russia; ORCID: ; e-mail: mlapina@ncfu.ru

Mikhail Babenko graduated in mathematics from Stavropol State University (SSU), in 2007, and the Ph.D. degree in mathematics from SSU, in 2011. He is currently the Head of the Department of Computational Mathematics and Cybernetics with North-Caucasus Federal University. He is the author of over 77 publications and five patents. His research interests include cloud computing, high-performance computing, residue number systems, neural networks, and cryptography.

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Paperback. Condition: new. Paperback. Cyber-physical systems (CPS) integrate computation, communication, control, and physical elements to achieve shared goals with minimal human intervention, encompassing smart technologies such as cities, cloud computing, and smart grids. As CPS components expand, generating vast amounts of data, they face challenges in areas like resource management, security, computation offloading, and automation, demanding advanced techniques beyond traditional algorithms. Nature-inspired optimization algorithms, drawing on natural phenomena, offer scalable and adaptable solutions for these complex issues, making them essential for addressing CPS challenges efficiently and enhancing their role in our daily lives. Nature-Inspired Optimization Algorithms for Cyber-Physical Systems provides relevant theoretical frameworks and the latest empirical research findings in the area. It explores the nature-inspired optimization algorithms intended to boost the performance of CPS. Covering topics such as ant colony optimization, data analysis, and smart cities, this book is an excellent resource for teaching staff, researchers, academicians, graduate and postgraduate students, and more. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9798369368350

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Paperback. Condition: new. Paperback. Cyber-physical systems (CPS) integrate computation, communication, control, and physical elements to achieve shared goals with minimal human intervention, encompassing smart technologies such as cities, cloud computing, and smart grids. As CPS components expand, generating vast amounts of data, they face challenges in areas like resource management, security, computation offloading, and automation, demanding advanced techniques beyond traditional algorithms. Nature-inspired optimization algorithms, drawing on natural phenomena, offer scalable and adaptable solutions for these complex issues, making them essential for addressing CPS challenges efficiently and enhancing their role in our daily lives. Nature-Inspired Optimization Algorithms for Cyber-Physical Systems provides relevant theoretical frameworks and the latest empirical research findings in the area. It explores the nature-inspired optimization algorithms intended to boost the performance of CPS. Covering topics such as ant colony optimization, data analysis, and smart cities, this book is an excellent resource for teaching staff, researchers, academicians, graduate and postgraduate students, and more. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9798369368350

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Paperback. Condition: new. Paperback. Cyber-physical systems (CPS) integrate computation, communication, control, and physical elements to achieve shared goals with minimal human intervention, encompassing smart technologies such as cities, cloud computing, and smart grids. As CPS components expand, generating vast amounts of data, they face challenges in areas like resource management, security, computation offloading, and automation, demanding advanced techniques beyond traditional algorithms. Nature-inspired optimization algorithms, drawing on natural phenomena, offer scalable and adaptable solutions for these complex issues, making them essential for addressing CPS challenges efficiently and enhancing their role in our daily lives. Nature-Inspired Optimization Algorithms for Cyber-Physical Systems provides relevant theoretical frameworks and the latest empirical research findings in the area. It explores the nature-inspired optimization algorithms intended to boost the performance of CPS. Covering topics such as ant colony optimization, data analysis, and smart cities, this book is an excellent resource for teaching staff, researchers, academicians, graduate and postgraduate students, and more. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. Seller Inventory # 9798369368350

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