Artificial Neural Networks for Renewable Energy Systems and Real World Applications is popular PDF and ePub book, written by Ammar Hamed Elsheikh in 2022-09-08, it is a fantastic choice for those who relish reading online the Technology & Engineering genre. Let's immerse ourselves in this engaging Technology & Engineering book by exploring the summary and details provided below. Remember, Artificial Neural Networks for Renewable Energy Systems and Real World Applications can be Read Online from any device for your convenience.
Artificial Neural Networks for Renewable Energy Systems and Real World Applications Book PDF Summary
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
Detail Book of Artificial Neural Networks for Renewable Energy Systems and Real World Applications PDF
- Author : Ammar Hamed Elsheikh
- Release : 08 September 2022
- Publisher : Academic Press
- ISBN : 9780128231869
- Genre : Technology & Engineering
- Total Page : 290 pages
- Language : English
- PDF File Size : 7,5 Mb
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