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Artificial Neural Networks for Renewable Energy Systems and Real-World Applications
Introduces the fundamentals of artificial intelligence and its applications in modeling, analysis and optimization of different energy systems and manufacturing processes
Ammar Hamed Elsheikh (Edited by), Mohamed Abd Elaziz (Edited by)
9780128207932, Elsevier Science
Paperback, published 21 September 2022
288 pages, Approx. 100 illustrations
22.9 x 15.2 x 1.9 cm, 0.45 kg
Artificial Neural Networks for Renewable Energy Systems and Real-World Applications presents current trends for the solution of complex engineering problems in the application, modeling, analysis, and optimization of different energy systems and manufacturing processes. With growing research catering to the applications of neural networks in specific industrial applications, this reference provides a single resource catering to a broader perspective of ANN in renewable energy systems and manufacturing processes. ANN-based methods have attracted the attention of scientists and researchers in different engineering and industrial disciplines, making this book a useful reference for all researchers and engineers interested in artificial networks, renewable energy systems, and manufacturing process analysis.
Part I: ANN fundamentals 1. Introduction 2. Basic Principles of ANNs 3. Types of ANNs Part II: Applications of ANNs in Renewable Energy Systems 4. Applications of ANN in Solar Collectors 5. Applications of ANN in Solar Water Desalination 6. Modeling of Solar Cells Using of ANN 7. Applications of ANN in Wind Energy 8. Applications of ANN in Biofuel Part III: Applications of ANNs in Manufacturing Processes 9. Applications of ANN in Machining 10. Applications of ANN in Metal forming 11. Applications of ANN in Welding 12. Applications of ANN in Industrial Robots
Subject Areas: Alternative & renewable energy sources & technology [THX]
