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Artificial Neural Networks for Renewable Energy Systems and Real-World Applications

Editat de Ammar Hamed Elsheikh, Mohamed Elasyed Abd Elaziz
Notă GoodReads:
en Limba Engleză Paperback – 21 Sep 2022
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.


  • Includes illustrative examples on the design and development of ANNS for renewable and manufacturing applications
  • Features computer-aided simulations presented as algorithms, pseudocodes and flowcharts
  • Covers ANN theory for easy reference in subsequent technology specific sections
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Specificații

ISBN-13: 9780128207932
ISBN-10: 0128207930
Pagini: 288
Ilustrații: Approx. 100 illustrations
Dimensiuni: 152 x 229 mm
Greutate: 0.39 kg
Editura: ELSEVIER SCIENCE

Cuprins

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