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RT Book, Whole SR Electronic DC OPAC T1 Data mining and machine learning in building energy analysis / Fr�ed�eric Magoul�es, Hai-Xiang Zhao T2 Computer engineering series A1 Magoul�es, F A1 Zhao, Haixiang 1973- YR 2016 FD 2016 SP 1 online resource (xiv, 164 pages K1 Data mining K1 Machine learning K1 Buildings -- Energy conservation -- Research K1 Buildings -- Energy conservation -- Mathematical models K1 Data Mining K1 Machine Learning K1 Constructions -- �Economies d'�energie -- Recherche K1 Exploration de donn�ees (Informatique) K1 Apprentissage automatique K1 Constructions -- �Economies d'�energie -- Mod�eles math�ematiques K1 COMPUTERS -- General K1 Buildings -- Energy conservation -- Mathematical models K1 Buildings -- Energy conservation -- Research K1 Data mining K1 Machine learning PB ISTE : Wiley PP London ; Hoboken, NJ SN 9781118577592 SN 1118577590 SN 9781118577691 SN 1118577698 SN 1118577485 SN 9781118577486 LA English (英語) CL LCC:QA76.9.D343 CL DC23:006.312 NO Includes bibliographical references and index NO "The energy performance in buildings is influenced by many factors, such as ambient weather conditions, building structure and characteristics, occupants and their behaviors, operation of sublevel components like heating, ventilation and air-conditioning systems. These complex properties make the prediction, analysis or fault detection/diagnosis of building energy consumption very difficult to perform accurately. This book focuses on up-to-date data mining and machine-learning methods to solve these problems."--Preface NO "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. The text also simulates energy consumption profiles for single and multiple buildings. Based on these datasets, Support Vector Machine (SVM) models are trained and tested to do the prediction. Suitable for novice, intermediate, and advanced readers, this is a vital resource for building designers, engineers, and students."--Provided by publisher NO Print version record NO Copyright � Wiley-ISTE 2016 NO John Wiley and Sons Wiley Online Library: Complete oBooks NO HTTP:URL=https://onlinelibrary.wiley.com/doi/book/10.1002/9781118577691 NO 書誌ID=EB00004466; LK [E Book]https://onlinelibrary.wiley.com/doi/book/10.1002/9781118577691 OL 30