Artificial Neural Networks for Renewable Energy Systems and Real-World Applications
- 1st Edition - September 21, 2022
- Editors: Ammar Hamed Elsheikh, Mohamed Abd Elaziz
- Language: English
- Paperback ISBN:9 7 8 - 0 - 1 2 - 8 2 0 7 9 3 - 2
- eBook ISBN:9 7 8 - 0 - 1 2 - 8 2 3 1 8 6 - 9
Artificial Neural Networks for Renewable Energy Systems and Real-World Applications presents current trends for the solution of complex engineering problems in the applicati… Read more
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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
Researchers in modelling, analysis, and economic evaluation for engineering systems
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
- Edition: 1
- Published: September 21, 2022
- Language: English
AE
Ammar Hamed Elsheikh
Ammar Elsheikh received the B.S. and M.S. degrees in mechanical engineering from Tanta university, Tanta, Egypt and Ph.D. degree from Huazhong university of science and technology, Wuhan, China. He is currently working as an associative professor in Tanta University and Tokyo Institute of Technology. He is one of the 2% influential scholars, which depicts the 100,000 top-scientists in the world. His research interests include renewable energy, manufacturing processes, and the application of artificial intelligence techniques in engineering problems.
Affiliations and expertise
Associate Professor, Tanta University, Tanta, Egypt; Associate Professor, Huazhong University of Science and Technology, Wuhan, ChinaMA
Mohamed Abd Elaziz
MOHAMED ABD ELAZIZ received the B.S. and M.S. degrees in Computer science from the Zagazig University, in 2008 and 2011, respectively. He received Ph.D. degree in mathematics and computer science from Zagazig University, Egypt in 2014. From 2008 to 2011, he was Assistant lecturer in Department of computer science. He is Program director of artificial intelligence science at Galala university, Egypt. He is the author of more than 200 articles. ABD ELAZIZ is one of the 2% influential scholars, which depicts the 100,000 top-scientists in the world. His research interests include metaheuristic technique, security IoT, cloud computing machine learning, signal processing, image processing, and evolutionary algorithms.
Affiliations and expertise
Program director of artificial intelligence science at Galala university, EgyptRead Artificial Neural Networks for Renewable Energy Systems and Real-World Applications on ScienceDirect