Research Article Open Access

An Efficient Weather Forecasting System using Radial Basis Function Neural Network

Tiruvenkadam Santhanam1 and A. C. Subhajini1
  • 1 ,
Journal of Computer Science
Volume 7 No. 7, 2011, 962-966

DOI: https://doi.org/10.3844/jcssp.2011.962.966

Submitted On: 11 March 2011 Published On: 28 June 2011

How to Cite: Santhanam, T. & Subhajini, A. C. (2011). An Efficient Weather Forecasting System using Radial Basis Function Neural Network. Journal of Computer Science, 7(7), 962-966. https://doi.org/10.3844/jcssp.2011.962.966

Abstract

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.

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Keywords

  • Multilayer perception
  • weather forecasting
  • rainfall prediction
  • Radial Basis Function (RBF)
  • back propagation
  • artificial neural network
  • Numerical Weather Prediction (NWP)