Prediction of Rainfall Using Backpropagation Neural Network Model
Journal Title: International Journal on Computer Science and Engineering - Year 2010, Vol 2, Issue 4
Abstract
Agriculture is the predominant occupation in India, accounting for about 52% of employment. The Irrigation acilities are nadequate, as revealed by the fact that only 52.6% of the land was irrigated in 2009–10 which result in farmers still being ependent on ainfall, specifically the Monsoon season. A good monsoon results in a robust growth for the economy as a hole, while a poor monsoon leads to a sluggish growth. . rtificial eural twork is one of the most widely used pervised echniques of data mining. In this paper we used the back ropagation eural network odel for predicting the rainfall based on humidity, dew point and pressure in the country INDIA. wo-Third of the data was used for training and ne-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. rom these results we can predict the rainfall for the future.
Authors and Affiliations
Enireddy. Vamsidhar , K. V. S. R. P. Varma , P. Sankara Rao , Ravikanth satapati
Keywords
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