TY  - JOUR
AU  - Santhanam, Tiruvenkadam 
AU  - Subhajini, A. C. 
PY  - 2011
TI  - An Efficient Weather Forecasting System using Radial Basis Function Neural Network
JF  - Journal of Computer Science
VL  - 7
IS  - 7
DO  - 10.3844/jcssp.2011.962.966
UR  - https://thescipub.com/abstract/jcssp.2011.962.966
AB  - 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.