Prediction of Rainfall using GRNN and Neurofuzzy Techniques

The weather, in India, fluctuates very frequently, which makes the rainfall prediction here an extremely puzzling task. Although there are many climatic and geographical parameters which decide the quantity of rainfall, the two very crucial parameters on which the rainfall strongly depends are the humidity and temperature. In the present paper, an attempt is done to forecast the quantity of rainfall for given minimum temperature, maximum temperature, and humidity. The techniques that are used to design prediction models are the RBF based ANN (GRNN) and the Neurofuzzy model. The prediction models are developed, in MATLAB, using both the techniques. The prediction result of both models is investigated on the basis of the available testing data, and their prediction errors are compared.