Estimation of Monthly Sunshine Duration in Turkey Using Artificial Neural Networks

Abstract

This paper introduces an artificial neural network (ANN) approach for estimating monthly mean daily values of global sunshine duration (SD) for Turkey. Three different ANN models, namely, GRNN, MLP, and RBF, were used in the estimation processes. A climatic variable (cloud cover) and two geographical variables (day length and month) were used as input parameters in order to obtain monthly mean SD as output. The datasets of 34 stations which spread across Turkey were split into two parts. First part covering 21 years (1980–2000) was used for training and second part covering last six years (2001–2006) was used for testing. Statistical indicators have shown that, GRNN and MLP models produced better results than the RBF model and can be used safely for the estimation of monthly mean SD.