Impact of predictor variables on the performance of future occupancy prediction: Feature selection using genetic algorithms and machine learning
Authors:
- Mohammad Esrafilian-NajafabadiMEMohammad Esrafilian-Najafabadi
- Fariborz HaghighatFariborz Haghighat
- 6 May 2022
- journal article
- research article
- Published by Elsevier in Building and Environment
- Vol. 219
Abstract
No abstract availableKeywords
This publication has 42 references indexed in Scilit:
- Modeling regular occupancy in commercial buildings using stochastic modelsEnergy and Buildings, 2015
- A survey on feature selection methodsComputers and Electrical Engineering, 2014
- Detecting outliers: Do not use standard deviation around the mean, use absolute deviation around the medianJournal of Experimental Social Psychology, 2013
- Occupancy-based zone-climate control for energy-efficient buildings: Complexity vs. performanceApplied Energy, 2013
- Optimization techniques in diesel engine system design2013
- Importance of occupancy information for building climate controlApplied Energy, 2013
- Genetic algorithm-based feature selection in high-resolution NMR spectraExpert Systems with Applications, 2008
- Process design and operation2004
- TOPSIS for MODMEuropean Journal of Operational Research, 1994
- Genetic AlgorithmsScientific American, 1992