Ecology, Environment and Conservation, ( ISI ), Volume (20), No (1), Year (2014-2) , Pages (241-245)

Title : ( Comparison of ANN and ARIMA techniques for forecasting Kardeh river flow )

Authors: Mahmood Sabouhi Sabouni , F. Rastegaripour , A. Ali Keykha , Saeed Reza Khodashenas , Mahmoud Okati ,

Citation: BibTeX | EndNote

Because of Iran located in climate of arid and semi-arid, prediction of river flow for programming and water resources management is very important.Present research was carried out with the aim of Kardeh river artificial flow production using neural network and ARIMA model, and evaluating performance of these two models. Data used in this research as monthly time series from 1987 to 2013 was collected from Regional Water Department of Mashhad. Quantity obtained from division of R2 index for all time durations in ANN model is more than 1 (> 1), that show index is higher for ANN model than ARIMA model. Also quantity obtained from division of RMSE, MSE and MAD indexes for all time duration is lower for ANN model than ARIMA model, however in this study, Kardeh river artificial flow production was Forecasted with use of method of artificial neural network

Keywords

, ARIMA, ANN, Forecasting,
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@article{paperid:1055359,
author = {Sabouhi Sabouni, Mahmood and F. Rastegaripour and A. Ali Keykha and Khodashenas, Saeed Reza and Mahmoud Okati},
title = {Comparison of ANN and ARIMA techniques for forecasting Kardeh river flow},
journal = {Ecology, Environment and Conservation},
year = {2014},
volume = {20},
number = {1},
month = {February},
issn = {0971-765X},
pages = {241--245},
numpages = {4},
keywords = {ARIMA; ANN; Forecasting; KardehRiver},
}

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%0 Journal Article
%T Comparison of ANN and ARIMA techniques for forecasting Kardeh river flow
%A Sabouhi Sabouni, Mahmood
%A F. Rastegaripour
%A A. Ali Keykha
%A Khodashenas, Saeed Reza
%A Mahmoud Okati
%J Ecology, Environment and Conservation
%@ 0971-765X
%D 2014

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