Soft Computing Techniques for Weather Change Predictions in Delhi

Abstract

Weather forecasting and warning is the application of science and technology to predict the state of the weather for a future time of a given location. The emergence of adverse effects of weather has endangered the life of general public in previous years. The unpredicted flood and super cyclone in many places have created havoc. The government and private agencies are working on its behaviours but still it is challenging and incomplete. But, the application of soft computing techniques in weather prediction has made a significant perfomance now a days. This research work presents the comparative study of soft computing techniques like MultiLayer Perceptron(MLP), Support Vector Machine(SVM) and J48 Decision Tree for forecasting the weather of Delhi with ten years data comprising of temperature, dew, humidity, air pressure, wind speed and visibility. This paper tries to describe the comparison among above models using four different error values like Relative Absolute Error(RAE), Mean Absolute Error(MAE), Root Mean Squared Error(RMSE) and Root Relative Squared Error(R2) with a proposed model by defining new algorithm. Further the performance can be enhanced if textmining will be applied in this proposed model.