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An Efficient Weather Forecasting System Using a Hybrid Neural Network SOFM–MLP with Modified LM

Dr. S. Santhosh Baboo, I. Kadar Shereef

Abstract


In this paper, primarily hybrid network is illustrated, which integrates a Self-Organizing Feature Map (SOFM) and a Multilayer Perceptron Network (MLP) to understand a much better prediction system. Then, it is demonstrated that the use of appropriate features can not only reduce the number of features, but also can improve the prediction accuracy. A feature selection MLP selects significant features online while learning the prediction task. Moreover, in this proposed approach, MLP is trained using Modified Levenberg-Marquardt algorithm for better convergence and performance. The experimental results show that the proposed approach provides significant prediction result with very less error rates.

Keywords


SOFM, MLP, Modified Levenberg-Marquardt, Prediction.

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References


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http://weather.uwyo.edu/cgi bin/wyowx.fcgi?TYPE=sflist&DATE=current&HOUR=current&UNITS=A&STATION=VOMM




DOI: http://dx.doi.org/10.36039/AA102011008

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