Data Mining and Machine Learning in Building Energy Analysis
Frederic Magoules
€ 179.03
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Description for Data Mining and Machine Learning in Building Energy Analysis
Hardback. Focusing on up-to-date artificial intelligence models to solve building energy problems, Artificial Intelligence for Building Energy Analysis reviews recently developed models for solving these issues, including detailed and simplified engineering methods, statistical methods, and artificial intelligence methods. Num Pages: 186 pages, black & white illustrations. BIC Classification: UYQ. Category: (P) Professional & Vocational. Dimension: 239 x 159 x 16. Weight in Grams: 434.
The energy consumption of a building has, in recent years, become a determining factor during its design and construction. With carbon footprints being a growing issue, it is important that buildings be optimized for energy conservation and CO2 reduction. This book therefore presents AI models and optimization techniques related to this application.
The authors start with a review of recent models for the prediction of building energy consumption: engineering methods, statistical methods, artificial intelligence methods, ANNs and SVMs in particular. The book then focuses on SVMs, by first applying them to building energy consumption, then presenting the principles and various ... Read more
Show LessProduct Details
Format
Hardback
Publication date
2016
Publisher
ISTE Ltd and John Wiley & Sons Inc United Kingdom
Number of pages
186
Condition
New
Number of Pages
186
Place of Publication
London, United Kingdom
ISBN
9781848214224
SKU
V9781848214224
Shipping Time
Usually ships in 7 to 11 working days
Ref
99-50
About Frederic Magoules
Frédéric Magoulès is Professor at the Ecole Centrale Paris in France and Honorary Professor at the University of Pècs in Hungary. His research focuses on parallel computing, numerical linear algebra and machine learning. Hai-Xiang Zhao is Senior Researcher at Amadeus in France. His research focuses on parallel computing, data mining and machine learning.
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