[Home ] [Archive]   [ فارسی ]  
:: Main :: About :: Current Issue :: Archive :: Search :: Submit :: Contact ::
:: Volume 2, Issue 4 (10-2008) ::
jwmseir 2008, 2(4): 74-77 Back to browse issues page
Comparison of Application Time Series and Artificial Neural Network Models in Drought Forecasting (Case Study: Khorasan Razavi Provinces) Indices
Ali Salajegheh , Abolhasan Fathabadi , Mansour Najafi Hajiva
in structor University of Tehran
Abstract:   (9074 Views)

Drought is the one of most important natural hazard which damages human social and natural environment

every year. For reducing the damage of drought future condition of drought should be forecasted. In

this study the application of time series and artificial neural network (PML) models in SPI value forecasting

were compared. First of all, SPI 3,6,9 and 12 were calculated then, by using artificial neural network

(PML) and time series models SPI values were forecasted. The results showed that time series model had

better application than neural network and SPI 9, 12 were better forecasted than SPI 3,6.

Keywords: Drought, Artificial Neural Network, Time Series, Khorasan Razavi and SPI Indices
Full-Text [PDF 154 kb]   (1212 Downloads)    
Type of Study: Research | Subject: Special
Received: 2013/01/27
Send email to the article author

Add your comments about this article
Your username or Email:

CAPTCHA code


XML   Persian Abstract   Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Salajegheh A, Fathabadi A, Najafi Hajiva M. Comparison of Application Time Series and Artificial Neural Network Models in Drought Forecasting (Case Study: Khorasan Razavi Provinces) Indices. jwmseir. 2008; 2 (4) :74-77
URL: http://jwmsei.ir/article-1-86-en.html


Volume 2, Issue 4 (10-2008) Back to browse issues page
مجله علوم ومهندسی آبخیزداری ایران Iranian Journal of Watershed Management Science and Engineering
Persian site map - English site map - Created in 0.05 seconds with 31 queries by YEKTAWEB 3742