Development of a model and forecasting of hourly uv index using artificial neural network (ANN) at Songkhla

Abstract

In this work, solar erythemal ultraviolet radiation (EUV) which affects human skin and skin cancer was investigated at Songkhla province (7.2°N, 100.6°E). EUV was converted to UV index, then the data was used for model development and forecasting of hourly UV index using Artificial Neural Network (ANN). The ANN model has one input layer, two hidden layers and one output layer. This input layer consists of extraterrestrial erythemal ultraviolet radiation, solar zenith angle, aerosol optical depth and cloud index which affect ultraviolet radiation, and the output layer is hourly UV index. The results show that hourly UV index obtained from ANN and that from the measurement are in reasonable agreement, with root mean square difference of 12.8% and mean bias difference of -2.4%. For forecasting of the hourly UV index, the data for 7 days earlier was used for forecasting the next UV index for one day or nine-hour (08:00 am.-16:00 pm.). Multi-layer perceptron and back propagation algorithm were used in the model forecasting. The results show that the UV index from the model forecasting is reasonable agrees with UV index from measurement with root mean square difference of 17.0% and mean bias difference of 0.3%.