Drought prediction has been playing important role in the planning management and using of water resources. In this research for drought predicting in 9 rain gauges station the Artificial Neural Network were used. The data used in this research is precipitation and the Standardized Precipitation Index (SPI), selected stations from 1972 to 2010 sets. The results obtained showed that among the Artificial Neural Networks models, in the most stations the Multi Layer Perceptron (MLP) has been able to predicting of SPI values with high correlation. Among the using stations, the Koohpayeh station showed the best action with correlation of r= 0.96 and RMSE= 0.04 and Ziyar station showed correlation of r= 0.86 and RMSE= 0.087, the lower performance than the other stations are shown.
Esfandyari,M , malekinezhad,H , Hakimzadeh,M and Afkhami,H . (2017). Application of Artificial Neural Network Models to Estimate Droughtness of
Isfahan Province. Extension and Development of Watershed Management, 5(16), 25-33.
MLA
Esfandyari,M , , malekinezhad,H , , Hakimzadeh,M , and Afkhami,H . "Application of Artificial Neural Network Models to Estimate Droughtness of
Isfahan Province", Extension and Development of Watershed Management, 5, 16, 2017, 25-33.
HARVARD
Esfandyari M, malekinezhad H, Hakimzadeh M, Afkhami H. (2017). 'Application of Artificial Neural Network Models to Estimate Droughtness of
Isfahan Province', Extension and Development of Watershed Management, 5(16), pp. 25-33.
CHICAGO
M Esfandyari, H malekinezhad, M Hakimzadeh and H Afkhami, "Application of Artificial Neural Network Models to Estimate Droughtness of
Isfahan Province," Extension and Development of Watershed Management, 5 16 (2017): 25-33,
VANCOUVER
Esfandyari M, malekinezhad H, Hakimzadeh M, Afkhami H. Application of Artificial Neural Network Models to Estimate Droughtness of
Isfahan Province. Extension and Development of Watershed Management. 2017;5(16):25-33 (In Persian).