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Applied Nature-Inspired Computing: Algorithms and Case Studies (Springer Tracts in Nature-Inspired Computing) - Softcover
Inhaltsangabe
This book presents a cutting-edge research procedure in the Nature-Inspired Computing (NIC) domain and its connections with computational intelligence areas in real-world engineering applications. It introduces readers to a broad range of algorithms, such as genetic algorithms, particle swarm optimization, the firefly algorithm, flower pollination algorithm, collision-based optimization algorithm, bat algorithm, ant colony optimization, and multi-agent systems. In turn, it provides an overview of meta-heuristic algorithms, comparing the advantages and disadvantages of each.
Moreover, the book provides a brief outline of the integration of nature-inspired computing techniques and various computational intelligence paradigms, and highlights nature-inspired computing techniques in a range of applications, including: evolutionary robotics, sports training planning, assessment of water distribution systems, flood simulation and forecasting, traffic control, gene expression analysis, antenna array design, and scheduling/dynamic resource management.
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Über die Autorin bzw. den Autor
Nilanjan Dey is an Assistant Professor in the Department of Information Technology at Techno India College of Technology, Kolkata, India. He is a visiting fellow of the University of Reading, UK. He was an honorary Visiting Scientist at Global Biomedical Technologies Inc., CA, USA (2012–2015). He was awarded his Ph.D. from Jadavpur University in 2015.
He has authored/edited more than 50 books with Elsevier, Wiley, CRC Press and Springer and published more than 300 papers. He is the Editor-in-Chief of International Journal of Ambient Computing and Intelligence, IGI Global, an Associated Editor of IEEE Access and International Journal of Information Technology, Springer. He is the Series Co-Editor of Springer Tracts in Nature-Inspired Computing, Springer Nature, the Series Co-Editor of Advances in Ubiquitous Sensing Applications for Healthcare, Elsevier and the Series Editor of Computational Intelligence in Engineering Problem Solving and Intelligent Signal Processingand Data Analysis, CRC.
His main research interests include Medical Imaging, Machine learning, Computer-Aided Diagnosis, Data Mining, etc. He is the Indian Ambassador of International Federation for Information Processing (IFIP) – Young ICT Group. Recently, he has been awarded as one among the top 10 most published academics in the field of Computer Science in India (2015–17).
Amira S. Ashour is currently an Assistant Professor and Head of Department-EEC, Faculty of Engineering, Tanta University, Egypt, since 2016. She has been the Vice Chair of Computer Engineering Department, Computers and Information Technology College, Taif University, KSA for one year from 2015. She has been the Vice Chair of CS Department, CIT College, Taif University, KSA for 5 years. Her research interests are Smart antenna, Direction of arrival estimation, Targets tracking, Image processing, Medical imaging, Machine learning, Signal/image/video processing, Image analysis, Computervision, and Optimization. She has 9 books and about 70 published journal papers. She is an Editor-in-Chief for the International Journal of Synthetic Emotions (IJSE), IGI Global, US and a Series Co-Editor of Advances in Ubiquitous Sensing Applications for Healthcare (AUSAH), Elsevier (Book Series). She is an Associate Editor for the IJRSDA, IGI Global, US as well as the IJACI, IGI Global, US. She is an Editorial Board Member of the International Journal of Image Mining (IJIM), Inderscience.
Siddhartha Bhattacharyya did his Bachelors in Physics, Bachelors in Optics and Optoelectronics and Masters in Optics and Optoelectronics from University of Calcutta, India in 1995, 1998 and 2000 respectively. He completed Ph.D. in Computer Science and Engineering from Jadavpur University, India in 2008. He is the recipient of the University Gold Medal from the University of Calcutta for his Masters. He is currently the Principal of RCC Institute of Information Technology, Kolkata, India. In addition, he is also serving as the Professor of Computer Application and Dean (Research and Development and Academic Affairs) of the institute. He is a Co-Authorco-author of 4 books and the Co-Editorco-editor of 8 books and has more than 185 research publications in international journals and conference proceedings to his credit. He has got a patent on intelligent colorimeter technology. He was the convener of the AICTE-IEEE National Conference on Computing and Communication Systems (CoCoSys-09) in 2009. He is the Membermember of the editorial board of Applied Soft Computing, Elsevier, B. V. He is serving as the Series Editor of the IGI Global Book Series Advances in Information Quality and Management (AIQM) from January 01, 2017. He is also Series Editor of the De Gruyter Book Series Frontiers in Computational Intelligence (FCI)from April 27, 2017. His research interests include soft computing, pattern recognition, multimedia data processing, hybrid intelligence and quantum computing. Dr. Bhattacharyya is a fellow of the Institute of Electronics and Telecommunication Engineers (IETE), India.
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This book presents a cutting-edge research procedure in the Nature-Inspired Computing (NIC) domain and its connections with computational intelligence areas in real-world engineering applications. It introduces readers to a broad range of algorithms, such as genetic algorithms, particle swarm optimization, the firefly algorithm, flower pollination algorithm, collision-based optimization algorithm, bat algorithm, ant colony optimization, and multi-agent systems. In turn, it provides an overview of meta-heuristic algorithms, comparing the advantages and disadvantages of each.
Moreover, the book provides a brief outline of the integration of nature-inspired computing techniques and various computational intelligence paradigms, and highlights nature-inspired computing techniques in a range of applications, including: evolutionary robotics, sports training planning, assessment of water distribution systems, flood simulation and forecasting, traffic control, gene expression analysis, antenna array design, and scheduling/dynamic resource management.
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Applied Nature-Inspired Computing: Algorithms and Case Studies
ISBN 10: 981139265X
ISBN 13: 9789811392658
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Taschenbuch. Zustand: Neu. Neuware -This book presents a cutting-edge research procedure in the Nature-Inspired Computing (NIC) domain and its connections with computational intelligence areas in real-world engineering applications. It introduces readers to a broad range of algorithms, such as genetic algorithms, particle swarm optimization, the firefly algorithm, flower pollination algorithm, collision-based optimization algorithm, bat algorithm, ant colony optimization, and multi-agent systems. In turn, it provides an overview of meta-heuristic algorithms, comparing the advantages and disadvantages of each.Moreover, the book provides a brief outline of the integration of nature-inspired computing techniques and various computational intelligence paradigms, and highlights nature-inspired computing techniques in a range of applications, including: evolutionary robotics, sports training planning, assessment of water distribution systems, flood simulation and forecasting, traffic control, gene expression analysis, antenna array design, and scheduling/dynamic resource management.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 288 pp. Englisch. Artikel-Nr. 9789811392658
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Applied Nature-Inspired Computing: Algorithms and Case Studies
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Springer Nature Singapore, Springer Nature Singapore, 2020
ISBN 10: 981139265X
ISBN 13: 9789811392658
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Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
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Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book presents a cutting-edge research procedure in the Nature-Inspired Computing (NIC) domain and its connections with computational intelligence areas in real-world engineering applications. It introduces readers to a broad range of algorithms, such as genetic algorithms, particle swarm optimization, the firefly algorithm, flower pollination algorithm, collision-based optimization algorithm, bat algorithm, ant colony optimization, and multi-agent systems. In turn, it provides an overview of meta-heuristic algorithms, comparing the advantages and disadvantages of each.Moreover, the book provides a brief outline of the integration of nature-inspired computing techniques and various computational intelligence paradigms, and highlights nature-inspired computing techniques in a range of applications, including: evolutionary robotics, sports training planning, assessment of water distribution systems, flood simulation and forecasting, traffic control, gene expression analysis, antenna array design, and scheduling/dynamic resource management. Artikel-Nr. 9789811392658
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Applied Nature-Inspired Computing: Algorithms and Case Studies (Springer Tracts in Nature-Inspired Computing)
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