Advances In Artificial Intelligence For Renewable Energy Systems And Energy Autonomy
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Advances in Artificial Intelligence for Renewable Energy Systems and Energy Autonomy
Author: Mukhdeep Singh Manshahia
language: en
Publisher: Springer Nature
Release Date: 2023-06-14
This book provides readers with emerging research that explores the theoretical and practical aspects of implementing new and innovative artificial intelligence (AI) techniques for renewable energy systems. The contributions offer broad coverage on economic and promotion policies of renewable energy and energy-efficiency technologies, the emerging fields of neuro-computational models and simulations under uncertainty (such as fuzzy-based computational models and fuzzy trace theory), evolutionary computation, metaheuristics, machine learning applications, advanced optimization, and stochastic models. This book is a pivotal reference for IT specialists, industry professionals, managers, executives, researchers, scientists, and engineers seeking current research in emerging perspectives in artificial intelligence, renewable energy systems, and energy autonomy.
AETA 2023—Recent Advances in Electrical Engineering and Related Sciences: Theory and Application
This book features selected papers from the 8th International Conference in Advanced Engineering—Theory Applications (AETA 2023), during 14–16 December, in Busan, Korea. The topics of the papers cover three main topics: energy (energy saving power electronics, electrical machines and drive systems, green-energy IT, nontrivial dynamics of electronic devices); control engineering (robotics, automatic control, biosensor IT); communication and security (broadcasting IT, communications, cyber security). Its content caters to researchers, scientist, and engineers who are interested in scientific achievements and advanced technologies of electrical, electronic-telecommunication, computer science, and mechanical-mechatronics engineering.
Computer Vision and Machine Intelligence for Renewable Energy Systems
Computer Vision and Machine Intelligence for Renewable Energy Systems offers a practical, systemic guide to the use of computer vision as an innovative tool to support renewable energy integration.This book equips readers with a variety of essential tools and applications: Part I outlines the fundamentals of computer vision and its unique benefits in renewable energy system models compared to traditional machine intelligence: minimal computing power needs, speed, and accuracy even with partial data. Part II breaks down specific techniques, including those for predictive modeling, performance prediction, market models, and mitigation measures. Part III offers case studies and applications to a wide range of renewable energy sources, and finally the future possibilities of the technology are considered. The very first book in Elsevier's cutting-edge new series Advances in Intelligent Energy Systems, Computer Vision and Machine Intelligence for Renewable Energy Systems provides engineers and renewable energy researchers with a holistic, clear introduction to this promising strategy for control and reliability in renewable energy grids. - Provides a sorely needed primer on the opportunities of computer vision techniques for renewable energy systems - Builds knowledge and tools in a systematic manner, from fundamentals to advanced applications - Includes dedicated chapters with case studies and applications for each sustainable energy source