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.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
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.
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.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 288 pp. Englisch. N° de réf. du vendeur 9780128207932
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Taschenbuch. Etat : Neu. Artificial Neural Networks for Renewable Energy Systems and Real-World Applications | Ammar Hamed Elsheikh (u. a.) | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2022 | Elsevier Inc | EAN 9780128207932 | Verantwortliche Person für die EU: Elsevier B.V., Radarweg 29, 1043 NX AMSTERDAM, NIEDERLANDE, productsafety[at]elsevier[dot]com | Anbieter: preigu. N° de réf. du vendeur 118923273
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Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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. N° de réf. du vendeur 9780128207932
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Etat : New. In English. N° de réf. du vendeur ria9780128207932_new
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Etat : New. 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 r. N° de réf. du vendeur 398132829
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