A Neural Network Model for Surface Air Temperature Estimation over the Eastern Part of Thailand in 2004

This paper investigates the use of an Artificial Neural Network (ANN) to estimate one year surface air temperature over the eastern part of Thailand in 2004. ANN's are becoming increasingly prominent in many areas of weather forecasting due to their potential to capture the complex relationships between the many factors that contribute to certain weather conditions. The estimations produced by the ANN's were compared to meteorological observation data by the Thai Meteorological Department. The results confirm that ANN's have the potential for successful application to the problem of surface air temperature estimation. The purpose of this study is studying influence of climate change which effected with air temperature in eastern part of Thailand. We have used soft computing approach such as ANN and the result of experimental is very well. We can use ANN technique to predict air temperature for 1 year ahead.