Nature-Inspired Methods for Metaheuristics Optimization / Modeling and Optimization in Science and Technologies Bd.16 (PDF)
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This book gathers together a set of chapters covering recent development in optimization methods that are inspired by nature. The first group of chapters describes in detail different meta-heuristic algorithms, and shows their applicability using some test or real-world problems. The second part of the book is especially focused on advanced applications and case studies. They span different engineering fields, including mechanical, electrical and civil engineering, and earth/environmental science, and covers topics such as robotics, water management, process optimization, among others. The book covers both basic concepts and advanced issues, offering a timely introduction to nature-inspired optimization method for newcomers and students, and a source of inspiration as well as important practical insights to engineers and researchers.
Prof. Rajib Kumar Bhattacharjya is a Professor in the Department of Civil Engineering at the Indian Institute of Technology Guwahati, India. He received his Bachelor's and Master's Degree in Civil Engineering from Gauhati University, India, in 1993 and 1995, respectively, and his Ph.D. in Civil Engineering from the Indian Institute of Technology Kanpur, India, in 2004. His research interests include classical and non-classical optimization methods, groundwater management, groundwater pollution control, and management of saltwater intrusion in coastal aquifers, as well as artificial neural networks and their applications in civil engineering. He has gained more than 20 years of teaching and research experience. He has authored more than 70 peer-reviewed scientific publications in renowned international journals and conference proceedings, and has served as a co-editor of two recent books i.e. "Urban Hydrology, Watershed
- 2020, 1st ed. 2020, 502 Seiten, Englisch
- Herausgegeben: Fouad Bennis, Rajib Kumar Bhattacharjya
- Verlag: Springer-Verlag GmbH
- ISBN-10: 3030264580
- ISBN-13: 9783030264581
- Erscheinungsdatum: 17.01.2020
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- Dateiformat: PDF
- Größe: 17 MB
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