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Advances of Artificial Intelligence in a Green Energy Environment reviews the new technologies in intelligent computing and AI that are reducing the dimension of data coverage worldwide. This handbook describes intelligent optimization algorithms that can be applied in various branches of energy engineering where uncertainty is a major concern.
Including AI methodologies and applying advanced evolutionary algorithms to real-world application problems for everyday life applications, this book considers distributed energy systems, hybrid renewable energy systems using AI methods, and new
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Produktbeschreibung
Advances of Artificial Intelligence in a Green Energy Environment reviews the new technologies in intelligent computing and AI that are reducing the dimension of data coverage worldwide. This handbook describes intelligent optimization algorithms that can be applied in various branches of energy engineering where uncertainty is a major concern.

Including AI methodologies and applying advanced evolutionary algorithms to real-world application problems for everyday life applications, this book considers distributed energy systems, hybrid renewable energy systems using AI methods, and new opportunities in blockchain technology in smart energy.

Covering state-of-the-art developments in a fast-moving technology, this reference is useful for engineering students and researchers interested and working in the AI industry.
Autorenporträt
Pandian Vasant is a Research Associate at MERLIN Research Centre, TDTU in Vietnam. He holds a PhD in Computational Intelligence, an MSc in Engineering Mathematics, and a BSc in Mathematics. His research interests include soft computing, hybrid optimization, holistic optimization, innovative computing, and applications.

J. Joshua Thomas is an Associate Professor at UOW Malaysia KDU Penang University College. He obtained his PhD (Intelligent Systems Techniques) from University Sains Malaysia, Penang, and master's degree from Madurai Kamaraj University, India. He is working with deep learning algorithms, specially targeting on graph convolutional neural networks and bidirectional recurrent neural networks for drug target interaction and image tagging with embedded natural language processing. His work involves experimental research with software prototypes and mathematical modeling and design.