Comparative analysis of artificial intelligence based methods for prediction of precipitation. case study: North cyprus

Abstract

Prediction of precipitation is important for design, management of water resources systems, planning, flood predicting and hydrological events. This study aimed to compare the performance of three different “Artificial Intelligence (AI)” techniques which are “Artificial Neural Network (ANN), Adaptive Neuro Fuzzy Inference System (ANFIS) and Least Square Support Vector Machine (LSSVM)” to estimate monthly rainfall in Kyrenia Station of Turkish Republic of Northern Cyprus (TRNC). The monthly data covering ten years’ precipitation were used for the predictions. The comparative results showed that the LSSVM model can cause a bit more reliable performance in regard to ANN and ANFIS.