RIVER DAILY FLOW PREDICTION USING NEURO-FUZZY MODEL (CASE STUDY: TALEGHAN WATERSHED)

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

TALI KHOSHK SADEGH; MOHSENI SARAVI MOHSEN; VAFAKHAH MEHDI; KHALIGHI SIGAROUDI SHAHRAM

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: JOURNAL OF WATERSHED MANAGEMENT RESEARCH Year:2015 | Volume:5 | Issue:10 Page(s): 56-67

Download Full-Text

Persian Verion

View:

831

Download:

Cites:

Information Journal Paper

Title

RIVER DAILY FLOW PREDICTION USING NEURO-FUZZY MODEL (CASE STUDY: TALEGHAN WATERSHED)

Author(s)

TALI KHOSHK SADEGH | MOHSENI SARAVI MOHSEN | VAFAKHAH MEHDI | KHALIGHI SIGAROUDI SHAHRAM | Issue Writer Certificate

Keywords

DAILY DISCHARGEQ2

NEURO-FUZZYQ2

FLOOD FORECASTINGQ2

TALEGHAN WATERSHEDQ2

Abstract

The most important issues of watershed management, is predicting hydrological processes. Using new models in this field can help to management and proper planning. In addition, predicting of river flow, especially in flood conditions, will allow the authorities to reduce flood damage with the preparation. One of the ways which have recently been used to predict and estimate the flow rate of rivers is NEURO-FUZZY model. NEURO-FUZZY with review and determine the relationships between inputs and output, estimate the desired output deals. In this study, the three years values of the daily rainfall and discharge of different stations in TALEGHAN WATERSHED were used as input to the NEURO-FUZZY model and according to the statistical coefficients (RMSE, R2 and E), the best structure and inputs composition of NEURO-FUZZY to predict the river flow was determined. Results demonstrated that the best estimates were of the Gaussian fuzzfier. Although different input modes, provided acceptable results, Best estimates with coefficients RMSE and R2 (training data 0.02 and 0.98-checking data 0.06 and 0.87), was discharge of Mehran and Joestan and previous day discharge of Garab and Dehdar. The results indicated that NEURO-FUZZY can predict the daily flow with high accuracy and can be used in watershed management and flood control.

Cites

No record.

References

No record.

Cite

APA: Copy

TALI KHOSHK, SADEGH, MOHSENI SARAVI, MOHSEN, VAFAKHAH, MEHDI, & KHALIGHI SIGAROUDI, SHAHRAM. (2015). RIVER DAILY FLOW PREDICTION USING NEURO-FUZZY MODEL (CASE STUDY: TALEGHAN WATERSHED). JOURNAL OF WATERSHED MANAGEMENT RESEARCH, 5(10), 56-67. SID. https://sid.ir/paper/230356/en

Vancouver: Copy

TALI KHOSHK SADEGH, MOHSENI SARAVI MOHSEN, VAFAKHAH MEHDI, KHALIGHI SIGAROUDI SHAHRAM. RIVER DAILY FLOW PREDICTION USING NEURO-FUZZY MODEL (CASE STUDY: TALEGHAN WATERSHED). JOURNAL OF WATERSHED MANAGEMENT RESEARCH[Internet]. 2015;5(10):56-67. Available from: https://sid.ir/paper/230356/en

IEEE: Copy

SADEGH TALI KHOSHK, MOHSEN MOHSENI SARAVI, MEHDI VAFAKHAH, and SHAHRAM KHALIGHI SIGAROUDI, “RIVER DAILY FLOW PREDICTION USING NEURO-FUZZY MODEL (CASE STUDY: TALEGHAN WATERSHED),” JOURNAL OF WATERSHED MANAGEMENT RESEARCH, vol. 5, no. 10, pp. 56–67, 2015, [Online]. Available: https://sid.ir/paper/230356/en

Related Journal Papers