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- Publisher: Woodhead Publishing
- ISBN-10: 0323903967
- ISBN-13: 9780323903967
- Format: 15.2 x 22.9 x 2.1 cm, softcover
- Language: English
- SAVE -10% with code: EXTRA
Artificial Intelligence for Renewable Energy Systems (e-book) (used book) | bookbook.eu
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Description
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.
EXTRA 10 % discount with code: EXTRA
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- Publisher: Woodhead Publishing
- ISBN-10: 0323903967
- ISBN-13: 9780323903967
- Format: 15.2 x 22.9 x 2.1 cm, softcover
- Language: English English
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.
Reviews