Data Mining and Machine Learning in Building Energy Analysis (Hardcover) (ISBN-13: 9781848214224)

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 extensions, and SVR. The authors then move on to RDP, which they use to determine building energy faults through simulation experiments before presenting SVR model reduction methods and the benefits of parallel computing. The book then closes by presenting some of the current research and advancements in the field.

Author: Frédéric Magoules,Hai-Xiang Zhao
ISBN-10: 1848214227
ISBN-13: 9781848214224
Publisher: Wiley-Iste
Language: English
Published: 07/01/2016
Pages: 186
Format: Hardcover
Weight: 0.97lbs
Size: 9.21h x 6.14w x 0.50d