COMPARISON OF THE GEN EXPRESSION PROGRAMMING, NONLINEAR TIME SERIES AND ARTIFICIAL NEURAL NETWORK IN ESTIMATING THE RIVER DAILY FLOW

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ZAMANI R.; AHMADI F.; RADMANESH F.

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Journal: Journal of Water and Soil Year:2015 | Volume:28 | Issue:6 Page(s): 1172-1182

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Title

COMPARISON OF THE GEN EXPRESSION PROGRAMMING, NONLINEAR TIME SERIES AND ARTIFICIAL NEURAL NETWORK IN ESTIMATING THE RIVER DAILY FLOW

Author(s)

ZAMANI R. | AHMADI F. | RADMANESH F. | Issue Writer Certificate

Keywords

MODELINGQ2

ARTIFICIAL INTELLIGENCEQ1

DAILY DISCHARGEQ2

KARUN RIVERQ2

Abstract

Today, the daily flow forecasting of rivers is an important issue in hydrology and water resources and thuscan be used the results of daily river flow MODELING in water resources management, droughts and flood smonitoring. In this study, due to the importance of this issue, using nonlinear time series models and artificialintelligence (Artificial Neural Network and Gen Expression Programming), the daily flow MODELING has been at the time interval (1981-2012) in the Armand hydrometric station on the KARUN RIVER. Armand station up streambasin is one of the most basins in the North Karun basin and includes four sub basins (Vanak, Middle Karun, Behesht abad and Kohrang).The results of this study shown that ARTIFICIAL INTELLIGENCE models have superior than nonlinear time series in flow daily simulation in the KARUN RIVER. As well as, MODELING and comparison of ARTIFICIAL INTELLIGENCE models showed that the Gen Expression Programming have evaluation criteria better than artificial neural network.

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APA: Copy

ZAMANI, R., AHMADI, F., & RADMANESH, F.. (2015). COMPARISON OF THE GEN EXPRESSION PROGRAMMING, NONLINEAR TIME SERIES AND ARTIFICIAL NEURAL NETWORK IN ESTIMATING THE RIVER DAILY FLOW. JOURNAL OF WATER AND SOIL (AGRICULTURAL SCIENCES AND TECHNOLOGY), 28(6), 1172-1182. SID. https://sid.ir/paper/141197/en

Vancouver: Copy

ZAMANI R., AHMADI F., RADMANESH F.. COMPARISON OF THE GEN EXPRESSION PROGRAMMING, NONLINEAR TIME SERIES AND ARTIFICIAL NEURAL NETWORK IN ESTIMATING THE RIVER DAILY FLOW. JOURNAL OF WATER AND SOIL (AGRICULTURAL SCIENCES AND TECHNOLOGY)[Internet]. 2015;28(6):1172-1182. Available from: https://sid.ir/paper/141197/en

IEEE: Copy

R. ZAMANI, F. AHMADI, and F. RADMANESH, “COMPARISON OF THE GEN EXPRESSION PROGRAMMING, NONLINEAR TIME SERIES AND ARTIFICIAL NEURAL NETWORK IN ESTIMATING THE RIVER DAILY FLOW,” JOURNAL OF WATER AND SOIL (AGRICULTURAL SCIENCES AND TECHNOLOGY), vol. 28, no. 6, pp. 1172–1182, 2015, [Online]. Available: https://sid.ir/paper/141197/en

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