Prediction of meteorological parameters by fuzzy acceptance matching system

Authors

20.1001.1.27174409.1397.1.1.3.4/DOR

Abstract

Predicting natural processes that do not behave accurately has always been one of the areas of human interest so that he can make better plans for himself with prior knowledge of what is happening. One of the most powerful tools in this regard are intelligent systems, especially fuzzy-neural networks. In this article, we intend to use this structure to predict the absolute amount of air humidity. The descending gradient method has been used to teach the parameters of the tali part of the fuzzy-neural network and the genetic algorithm has been used for the parameters of the front part of the network so that the cost function is considered with the aim of minimizing the sum of squares of error.

















 

 


 

Keywords

References

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History

  • Receive Date: 01 December 2018
  • Revise Date: 21 January 2019
  • Accept Date: 21 January 2019

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