Variable selection methods for water demand forecasting in Ethiopia: Case study Gondar town

Abstract

Abstract This study developed variable selection methods to forecast urban water demand of Gondar town. Seven variable selection methods are adopted to develop appropriate water demand forecasting model. Multiple linear regression analysis was used to investigate in identifying the optimal predictor variable for developing the water demand forecasting model. The results showed that PCA played a big role to identify the influential variables in modeling of water demand in a better way as compared to other statistical methods. We developed three models to forecast the demand of water in the study area. This study selected Model 1 since Model 1 gives accurate results as compared to Model 2 and Model 3.