M5 model tree and gene expression programming for the prediction of metrological parameters

Metrological parameter prediction is an important task carried out by metrological researchers and water resource analyst for the estimation of water demand, water resource planning, management and operation. Accurate predictions of these parameters are still an open problem. M5 model tree and gene expression programming are two popular machine learning techniques which are considered as white-box model. In this paper, we have applied two machine learning techniques, such as M5 model tree and gene expression programming, for the prediction of various metrological parameters at a weather station. Among these two techniques, one is better over other for the prediction of a set of parameters.