Paper Information

Journal:   JOURNAL OF GEOGRAPHICAL SCIENCES   FALL 2012 , Volume 12 , Number 26; Page(s) 47 To 63.
 
Paper: 

FORECASTING ISFAHAN PRECIPITATION WITH ARTIFICIAL NEURAL NETWORKS

 
 
Author(s):  HALABIAN AMIR HOSSIEN, DARAND MOHAMMAD
 
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Abstract: 

Precipitation is the most important climate and meteorology factor. In this study monthly precipitation data of Isfahan synoptic station during 1951-2009 has been used. Because of none linearly of precipitation during time, The Artificial neural networks have been used.495 (70%) of data has been used as training and 231 data about (30%) as testing and validation. The Results of this study after network testing with different hidden layer and training coefficient indicated that using of artificial neural network with 2 hidden layer Perceptron, 0/4 training coefficient has presentation comparatively a better model. So after testing again network and training with different hidden layer and training coefficient in combination with genetic algorithm indicated that combination of network with mentioned characters with genetic algorithm decrease the error and increase speed of calculation and present a better model. The random and arranged precipitation data didn’t have any effect on the results. It is necessary to be mentioned that data combination neural networks with algorithm genetic result in increased accuracy and better fitting the model.

 
Keyword(s): PRECIPITATION, FORECASTING, ARTIFICIAL NEURAL NETWORK, GENETIC ALGORITHM, ISFAHAN
 
References: 
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