Computational Intelligence Methods for Green Technology and Sustainable Development - Proceedings of the International Conference GTSD2020 (Paperback, 1st ed. 2021)

This book is a selected collection of 54 peer-reviewed original scientific research papers of the 5th International Conference on Green Technology and Sustainable Development (GTSD2020) organised in Vietnam in 2020. It highlights the importance of sustainability as well as promotes up-to-date innovation and research for green development in technologies, economics and education among countries. The conference provides an international platform for researchers, practitioners, policymakers and entrepreneurs to present their advances, knowledge and experience on various interdisciplinary topics related to the theme of "Green technology and sustainable development in industrial revolution 4.0". The book is a valuable resource for researchers, analysts, engineers, practitioners and policymakers who are interested in the latest findings in artificial intelligence, cyber systems, robotics, green energy and power systems, mechanical and computational mechanic models and advanced civil engineering. This book has 05 sessions consisting of both theoretical and practical aspects, and numerical and experimental analyses in various engineering disciplines.

General

Imprint:	Springer Nature Switzerland AG
Country of origin:	Switzerland
Series:	Advances in Intelligent Systems and Computing, 1284
Release date:	October 2020
First published:	2021
Editors:	Yo-Ping Huang • Wen-June Wang • Hoang An Quoc • Le Hieu Giang • Nguyen-Le Hung
Dimensions:	235 x 155mm (L x W)
Format:	Paperback
Pages:	651
Edition:	1st ed. 2021
ISBN-13:	978-3-03-062323-4
Categories:	Books > Professional & Technical > Energy technology & engineering > Alternative & renewable energy sources & technology Books > Professional & Technical > Energy technology & engineering > Electrical engineering > General Books > Computing & IT > Applications of computing > Artificial intelligence > General Promotions
LSN:	3-03-062323-8
Barcode:	9783030623234

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