International Journal of Computer Applications |
Foundation of Computer Science (FCS), NY, USA |
Volume 85 - Number 15 |
Year of Publication: 2014 |
Authors: Seema Mahajan, Himanshu Mazumdar |
10.5120/14921-3518 |
Seema Mahajan, Himanshu Mazumdar . A Fast Learning Algorithm for Rainfall Prediction. International Journal of Computer Applications. 85, 15 ( January 2014), 37-40. DOI=10.5120/14921-3518
A PC based application is developed using 51 years of Indian rainfall data for long range prediction of average rain fall. This learning algorithm iteratively estimates 96 coefficients of a 5th order polynomial in few minutes. Proposed prediction model is based on modelling of time series rainfall data using 5th order non-linear predicting code. Steepest descent algorithm is used for extraction of appropriate coefficient of rainfall time series data. These coefficients are reinforced in model learning process. The rainfall data of 1960 to 2010 is used for the development of the model. Model has been tested on rainfall data for different training sets. The proposed model is capable of forecasting yearly rainfall 1 year in advance. Rainfall estimation accuracy is above 85%.