Data Mining and Machine Learning in Building Energy Analysis – Towards High Performance Computing
Seiten
2016
John Wiley & Sons Inc (Hersteller)
978-1-118-57769-1 (ISBN)
John Wiley & Sons Inc (Hersteller)
978-1-118-57769-1 (ISBN)
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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.
Frederic Magoules is Professor at the Ecole Centrale Paris in France and Honorary Professor at the University of Pecs 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.
| Erscheint lt. Verlag | 8.1.2016 |
|---|---|
| Verlagsort | New York |
| Sprache | englisch |
| Maße | 188 x 233 mm |
| Gewicht | 1442 g |
| Themenwelt | Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik |
| ISBN-10 | 1-118-57769-8 / 1118577698 |
| ISBN-13 | 978-1-118-57769-1 / 9781118577691 |
| Zustand | Neuware |
| Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
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