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

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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  • Language:
  • English
  • ISBN:
  • 9780128207932
  • Binding:
  • Paperback
  • Pages:
  • 288
  • Published:
  • September 20, 2022
  • Dimensions:
  • 227x153x26 mm.
  • Weight:
  • 486 g.
Delivery: 2-4 weeks
Expected delivery: July 13, 2025

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

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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