An Application of Time Series Analysis for Weather Forecasting

Weather forecasting has been one of the most challenging problems around the world for more than half a century. Not only because of its practical values in meteorology, but it is also a typical unbiased time series forecasting problem in scientific research. This paper utilizes artificial neural network (ANN) simulated in MATLAB to predict two important weather parameters i.e. maximum and minimum temperature. The model has been trained using past 60 years of data (1901-1960) and tested over 40 years to forecast maximum and minimum temperature. The results based on mean square error function (MSE) confirm, this model which is based on multilayer perceptron has the potential to successful application to weather forecasting.