Prediction of Rainfall Using Backpropagation Neural Network Model

摘要

Agriculture is the predominant occupation in India, accounting for about 52% of employment. The Irrigation facilities are inadequate, as revealed by the fact that only 52.6% of the land was irrigated in 2009?10 which result in farmers still being dependent on rainfall, specifically the Monsoon season. A good monsoon results in a robust growth for the economy as a whole, while a poor monsoon leads to a sluggish growth. . Artificial neural network is one of the most widely used supervised techniques of data mining. In this paper we used the back propagation neural network model for predicting the rainfall based on humidity, dew point and pressure in the country INDIA. Two-Third of the data was used for training and One-third for testing .The number of training and testing patterns are 250 training and 120 testing .In the training we obtained 99.79% of accuracy and in Testing we obtained 94.28% of accuracy. From these results we can predict the rainfall for the future.