Artificial Neural Networks for Renewable Energy Systems and Real-World Applications-电子书百科大全

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

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

Author(s): Elsheikh (Editor), Abd Elaziz

Publisher: Academic Press
Publication Date: 21 Sept. 2022
Edition: 1st
Language: English
Print length: 288 pages
ISBN-10: 0128207930
ISBN-13: 9780128207932

Book Description

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

Editorial Reviews

Review

Introduces the fundamentals of artificial intelligence and its applications in modeling, analysis and optimization of different energy systems and manufacturing processes

From the Back Cover

The applications of Artificial Neural Networks (ANN) in different engineering disciplines have attracted the attention of researchers to solve complex engineering problems that cannot be solved through conventional methods. 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 ANN in renewable energy systems and manufacturing processes.

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