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Artificial Intelligence for Renewable Energy systems (Paperback) Loot Price: R5,195
Discovery Miles 51 950
Artificial Intelligence for Renewable Energy systems (Paperback): Ashutosh Kumar Dubey, Sushil Narang, Arun Lal Srivastav,...

Artificial Intelligence for Renewable Energy systems (Paperback)

Ashutosh Kumar Dubey, Sushil Narang, Arun Lal Srivastav, Abhishek Kumar, Vicente Garcia Diaz

Series: Woodhead Publishing Series in Energy

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Loot Price R5,195 Discovery Miles 51 950 | Repayment Terms: R487 pm x 12*

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Artificial Intelligence for Renewable Energy Systems addresses the energy industries remarkable move from traditional power generation to a cost-effective renewable energy system, and most importantly, the paradigm shift from a market-based cost of the commodity to market-based technological advancements. Featuring recent developments and state-of-the-art applications of artificial intelligence in renewable energy systems design, the book emphasizes how AI supports effective prediction for energy generation, electric grid related line loss prediction, load forecasting, and for predicting equipment failure prevention. Looking at approaches in system modeling and performance prediction of renewable energy systems, this volume covers power generation systems, building service systems and combustion processes, exploring advances in machine learning, artificial neural networks, fuzzy logic, genetic algorithms and hybrid mechanisms.

General

Imprint: Woodhead Publishing Ltd
Country of origin: United States
Series: Woodhead Publishing Series in Energy
Release date: August 2022
First published: 2022
Editors: Ashutosh Kumar Dubey • Sushil Narang • Arun Lal Srivastav • Abhishek Kumar • Vicente Garcia Diaz
Dimensions: 229 x 152mm (L x W)
Format: Paperback
Pages: 406
ISBN-13: 978-0-323-90396-7
Categories: Books > Arts & Architecture > Architecture > Architectural structure & design
Books > Professional & Technical > Energy technology & engineering > Alternative & renewable energy sources & technology
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LSN: 0-323-90396-7
Barcode: 9780323903967

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