Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4914133 | Energy and Buildings | 2017 | 42 Pages |
Abstract
The performance of the proposed heuristic method is compared to two of the best algorithms used in the field, such as GRASP for feature selection and NSGA-II (Non-dominated Sorting Genetic Algorithm). The application on a real case study demonstrates that the proposed method solves the problem of feature selection in building performance estimation efficiently and reliably. Moreover, the model creation is automatic, making it ideal for integration into a Building Management System (BMS) in order to detect faults and perform short-term predictive control.
Related Topics
Physical Sciences and Engineering
Energy
Renewable Energy, Sustainability and the Environment
Authors
Daniele Antonucci, Ulrich Filippi Oberegger, Wilmer Pasut, Andrea Gasparella,