Click for new scientific resources and news about Corona[COVID-19]

Paper Information

Journal:   IRRIGATION SCIENCES AND ENGINEERING (JISE) (SCIENTIFIC JOURNAL OF AGRICULTURE)   SUMMER 2017 , Volume 40 , Number 2 ; Page(s) 59 To 73.
 
Paper: 

COMPARISON OF ARTIFICIAL NEURAL NETWORK (ANN) AND SDSM MODEL TO DOWNSCALING OF TEMPERATURE

 
 
Author(s):  SHEIDAEIAN M.*, ZIATABAR AHMADI M.KH., FAZLOULA R.
 
* GORGAN UNIVERSITY OF AGRICULTURAL SCIENCES AND NATURAL RESOURCES
 
Abstract: 

In this study downscaling of temperature was down in Tajan Plain located in the province of Mazandaran. The result of atmospheric general circulation models was obtained with HadCM3 climate model under scenario A2. Since the output of atmospheric general circulation models has a low locative resolution, should be downscaled in the area or Basin level that it was conducted with statistical method. The statistical methods used included of downscaling SDSM 5.5. And artificial neural network model. In this study, by using the average daily temperature data of Kordkheil Station during the30-year statistic Period (1971-2001) and the large-scale variables NCEP, as inputs to the neural network and SDSM model, simulation and downscaling was down respectively of the maximum and minimum temperature in the last period to determine models error. To this end were used of the features and functions available in the programming software MATLAB. Then To evaluate the performance of the models, were used the statistical criteria including of correlation coefficient, coefficient of declaration and root mean square error between observed and predicted values of temperature. The obtained results show the appropriate performance of SDSM model for downscaling temperature Than the ANN model. So that the error percentage of SDSM model is lower and the correlation coefficient is more than the ANN model. The best Structure of neural network to simulate of maximum temperature is perceptron model with four hidden layer with the 5-5-6-6 architecture and for the minimum temperature Variable is perceptron model with three hidden layer with 5.3.1 architecture.

 
Keyword(s): PROVINCE OF MAZANDARAN, HADCM3 MODEL, MATLAB, ATMOSPHERIC GENERAL CIRCULATION MODEL
 
References: 
  • ندارد
 
  Persian Abstract Yearly Visit 60
 
Latest on Blog
Enter SID Blog