Rainfall Prediction using Subtractive Clustering and Levenberg-Marquardt Algorithms

The subject of present paper is the rainfall prediction with knowledge of two input parameters on which the rainfall is strongly connected i.e temperature and humidity. The rainfall forecasting, in India, is a challenging task due to significantly fluctuating nature of weather here. In the present work, artificial intelligence (AI) techniques are used to train a prediction model for the forecasting of the amount of rainfall. The two considered input parameters, for this model, are temperature and humidity. The prediction models have been designed, using MATLAB, using two different AI approaches, one is the subtractive clustering and another is the Levenberg-Marquardt algorithm. Finally, their prediction performance is considered.