An Efficient Weather Forecasting System using Radial Basis Function Neural Network
Tiruvenkadam Santhanam and A. C. Subhajini
DOI : 10.3844/jcssp.2011.962.966
Journal of Computer Science
Volume 7, Issue 7
Problem statement: Accurate weather forecasting plays a vital role for planning day to day activities. Neural network has been use in numerous meteorological applications including weather forecasting. Approach: A neural network model has been developed for weather forecasting, based on various factors obtained from meteorological experts. This study evaluates the performance of Radial Basis Function (RBF) with Back Propagation (BPN) neural network. The back propagation neural network and radial basis function neural network were used to test the performance in order to investigate effective forecasting technique. Results: The prediction accuracy of RBF was 88.49%. Conclusion: The results indicate that proposed radial basis function neural network is better than back propagation neural network.
© 2011 Tiruvenkadam Santhanam and A. C. Subhajini. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.