Renewable energy is crucial to preserve the environment. This energy involves various systems that must be optimized and assessed to provide better performance; however, the design and development of renewable energy systems remains a challenge. It is crucial to implement the latest innovative research in the field in order to develop and improve renewable energy systems.
Applications of Nature-Inspired Computing in Renewable Energy Systems discusses the latest research on nature-inspired computing approaches applied to the design and development of renewable energy systems and provides new solutions to the renewable energy domain. Covering topics such as microgrids, wind power, and artificial neural networks, it is ideal for engineers, industry professionals, researchers, academicians, practitioners, teachers, and students.
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Mohamed Arezki Mellal is a Professor in the Department of Mechanical Engineering, Faculty of Technology, at M’Hamed Bougara University, Boumerdes, Algeria. He was ranked among the Top 2% of Scientists Worldwide by Stanford University (Single-year 2022) and was the top-ranked candidate in the 47th National University Commission for the Professorship in Mechanical Engineering in 2022. He has been a Visiting Scholar at various universities and has published over 80 research papers. He has been invited to various conferences and serves as a regular reviewer for over 30 SCIE journals.
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Renewable energy is crucial to preserve the environment. This energy involves various systems that must be optimized and assessed to provide better performance; however, the design and development of renewable energy systems remains a challenge. It is crucial to implement the latest innovative research in the field in order to develop and improve renewable energy systems. Applications of Nature-Inspired Computing in Renewable Energy Systems discusses the latest research on nature-inspired computing approaches applied to the design and development of renewable energy systems and provides new solutions to the renewable energy domain. Covering topics such as microgrids, wind power, and artificial neural networks, it is ideal for engineers, industry professionals, researchers, academicians, practitioners, teachers, and students. Seller Inventory # 9781799885627
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