Applications of Nature-Inspired Computing in Renewable Energy Systems
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| Title: | Applications of Nature-Inspired Computing in Renewable Energy Systems |
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| Description: | 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. |
| Authors: | Mohamed Arezki Mellal |
| Resource Type: | eBook. |
| Subjects: | Renewable energy sources--Data processing, Natural computation--Industrial applications |
| Categories: | TECHNOLOGY & ENGINEERING / Power Resources / Alternative & Renewable, SCIENCE / Energy, TECHNOLOGY & ENGINEERING / Environmental / General |
| Database: | eBook Collection (EBSCOhost) |
| Abstract: | 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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| ISBN: | 9781799885610 9781799885634 9781799885641 |
