Accurately predicting building energy performance using evolutionary multivariate adaptive regression splines
We propose EMARS by fusing multivariate adaptive regression splines (MARS) and artificial bee colony (ABC). We investigate EMARS performance in predicting cooling load (CL) and heating load (HL) of buildings. We use EMARS to find mapping functions of HL and CL with their input variables. Surface area and roof area are identified as the critical factors influencing HL of buildings. Statistical results found EMARS to provide significant prediction accuracy compared to other methods.
multivariate adaptive regression splines artificial bee colony cooling load heating load artificial intelligence energy performance of buildings