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Paper Information

Journal:   JOURNAL OF WATER AND SOIL CONSERVATION (JOURNAL OF AGRICULTURAL SCIENCES AND NATURAL RESOURCES)   2011 , Volume 18 , Number 1; Page(s) 231 To 240.
 
Paper: 

ASSESSING THE EFFICIENCY OF ARTIFICIAL NEURAL NETWORK FOR INTELLIGENT ESTIMATION OF FLOOD HYDROGRAPH OF JAFAR ABAD RIVER IN GORGAN

 
 
Author(s):  PAHLAVANI H., BAHREMAND A., DEHGHANI A.A.*, SADODDIN A.
 
* DEPT. OF WATER ENGINEERING, GORGAN UNIVERSITY OF AGRICULTURAL SCIENCES AND NATURAL RESOURCES
 
Abstract: 

Artificial neural network is a powerful tool to solve the engineering and technical problems such as water resource problems. In this study, the ability of neural network model for simulating the hydrograph in Jafar Abad River was evaluated. It is notable that the flood hydrograph was estimated 2, 3, 4 and 5 hours earlier using the flood discharges at 2, 3, 4 and 5 previous hours as model inputs respectively. This was carried out using 18 flood hydrographs recorded in upstream gauging station. From this dataset, 12 flood hydrographs were chosen to train the model and 6 flood hydrographs for validation and test the model. The results showed that by increasing the estimation lag time, the accuracy of results decreased and in a given lag time, by increasing the number of input, the accuracy of results increased. The results showed that the amount of efficiency coefficients, which is the representation of performance of flood hydrograph modeling, is 0.92 and 0.93 for two test hydrograph, respectively. The results also showed that the type of transfer function and learning algorithm were the effective factors on model outputs.

 
Keyword(s): FLOOD HYDROGRAPH, ARTIFICIAL NEURAL NETWORK, TRANSFER FUNCTION, JAFAR ABAD RIVER, GOLESTAN PROVINCE
 
 
References: 
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Citations: 
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+ Click to Cite.
APA: Copy

PAHLAVANI, H., & BAHREMAND, A., & DEHGHANI, A., & SADODDIN, A. (2011). ASSESSING THE EFFICIENCY OF ARTIFICIAL NEURAL NETWORK FOR INTELLIGENT ESTIMATION OF FLOOD HYDROGRAPH OF JAFAR ABAD RIVER IN GORGAN. JOURNAL OF WATER AND SOIL CONSERVATION (JOURNAL OF AGRICULTURAL SCIENCES AND NATURAL RESOURCES), 18(1), 231-240. https://www.sid.ir/en/journal/ViewPaper.aspx?id=275438



Vancouver: Copy

PAHLAVANI H., BAHREMAND A., DEHGHANI A.A., SADODDIN A.. ASSESSING THE EFFICIENCY OF ARTIFICIAL NEURAL NETWORK FOR INTELLIGENT ESTIMATION OF FLOOD HYDROGRAPH OF JAFAR ABAD RIVER IN GORGAN. JOURNAL OF WATER AND SOIL CONSERVATION (JOURNAL OF AGRICULTURAL SCIENCES AND NATURAL RESOURCES). 2011 [cited 2021July24];18(1):231-240. Available from: https://www.sid.ir/en/journal/ViewPaper.aspx?id=275438



IEEE: Copy

PAHLAVANI, H., BAHREMAND, A., DEHGHANI, A., SADODDIN, A., 2011. ASSESSING THE EFFICIENCY OF ARTIFICIAL NEURAL NETWORK FOR INTELLIGENT ESTIMATION OF FLOOD HYDROGRAPH OF JAFAR ABAD RIVER IN GORGAN. JOURNAL OF WATER AND SOIL CONSERVATION (JOURNAL OF AGRICULTURAL SCIENCES AND NATURAL RESOURCES), [online] 18(1), pp.231-240. Available: https://www.sid.ir/en/journal/ViewPaper.aspx?id=275438.



 
 
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