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Handbook of Intelligent Computing and Optimization for Sustainable Development by Mukhdeep Singh Manshahia (Hardback)
£271.95
Available
Product Ref. (e.g. ISBN, SKU)
9781119791829
Published:
25 Mar 2022
Format:
Hardback
Number of pages:
944 pages
Dimensions:
10x10x10mm
Weight:
0.454kgs
Author:
This work provides a comprehensive overview of the latest breakthroughs and recent progress in sustainable intelligent computing technologies, applications, and optimisation techniques across various industries.
HANDBOOK OF INTELLIGENT COMPUTING AND OPTIMIZATION FOR SUSTAINABLE DEVELOPMENT
This book provides a comprehensive overview of the latest breakthroughs and recent progress in sustainable intelligent computing technologies, applications, and optimization techniques across various industries.
Optimization has received enormous attention along with the rapidly increasing use of communication technology and the development of user-friendly software and artificial intelligence. In almost all human activities, there is a desire to deliver the highest possible results with the least amount of effort. Moreover, optimization is a very well-known area with a vast number of applications, from route finding problems to medical treatment, construction, finance, accounting, engineering, and maintenance schedules in plants. As far as optimization of real-world problems is concerned, understanding the nature of the problem and grouping it in a proper class may help the designer employ proper techniques which can solve the problem efficiently. Many intelligent optimization techniques can find optimal solutions without the use of objective function and are less prone to local conditions.
The 41 chapters comprising the Handbook of Intelligent Computing and Optimization for Sustainable Development by subject specialists, represent diverse disciplines such as mathematics and computer science, electrical and electronics engineering, neuroscience and cognitive sciences, medicine, and social sciences, and provide the reader with an integrated understanding of the importance that intelligent computing has in the sustainable development of current societies. It discusses the emerging research exploring the theoretical and practical aspects of successfully implementing new and innovative intelligent techniques in a variety of sectors, including IoT, manufacturing, optimization, and healthcare.
Audience
It is a pivotal reference source for IT specialists, industry professionals, managers, executives, researchers, scientists, and engineers seeking current research in emerging perspectives in the field of artificial intelligence in the areas of Internet of Things, renewable energy, optimization, and smart cities.
About the Author: Mukhdeep Singh Manshahia, PhD, is an assistant professor at Punjabi University Patiala, India. He has published more than 40 international and national research papers and edited 1 book. Valeriy Kharchenko, PhD, is the Chief Scientific Officer at the Federal Scientific Agro Engineering Center VIM, Moscow, Russia. Elias Munapo, PhD, is a full professor in the Department of Statistics & Operations Research, North West University, South Africa. He has published more than 100 research articles and book chapters and has edited several volumes. J. Joshua Thomas, PhD, is a senior lecturer at UOW Malaysia KDU Penang University College, Malaysia. Currently, he is working with machine learning, big data, data analytics, deep learning, specifically targeting convolutional neural networks (CNN) and bi-directional recurrent neural networks (RNN) for image tagging with embedded natural language processing, end-to-end steering learning systems, and GAN. He has published more than 40 papers in leading international conference proceedings and peer-reviewed journals. Pandian Vasant, PhD, is a professor at Universiti Teknologi PETRONAS, Malaysia. He has co-authored more than 250 research articles in journals, conference proceedings, presentations, special issues guest editor, book chapters, and is the Editor-in-Chief of International Journal of Energy Optimization & Engineering.
| Number of pages | 944 |
|---|
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