A PERFORMANCE EVALUATION OF NEURO-FUZZY AND REGRESSION METHODS IN ESTIMATION OF SEDIMENT LOAD OF RIVER

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.

VARVANI J.; EBRAHIMI N.; YOSEFI M.; SHADMANI M.R.; NIKCHE FARAHANI SH.

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

Journal Paper

Paper Information

Journal: Watershed Management Research Year:2016 | Volume:28 | Issue:109 Page(s): 104-113

Download Full-Text

Persian Verion

View:

752

Download:

Cites:

Information Journal Paper

Title

A PERFORMANCE EVALUATION OF NEURO-FUZZY AND REGRESSION METHODS IN ESTIMATION OF SEDIMENT LOAD OF RIVER

Author(s)

Keywords

TREE REGRESSIONQ2

NEURO-FUZZYQ2

SEDIMENT RATING CURVEQ2

SUSPENDED LOADQ2

Abstract

Application of NEURO-FUZZY and TREE REGRESSION models is not too old in hydrology of river sediments and also in watersheds and in this regard, SEDIMENT RATING CURVEs have been identified as the most common method for estimating sediment. In this study for comparison and correction of estimation methods of river sediment load, estimated rates of several uni-variate types of SEDIMENT RATING CURVEs and a multivariate type of SEDIMENT RATING CURVEs were investigated with NEURO-FUZZY and TREE REGRESSION models in five selective hydro-metric station of different climatic zones of Iran and with various indexes of the accuracy and the precision. The results show that the mean of the accuracy index of NEURO-FUZZY and TREE REGRESSION models in selective stations are 151 and 536 percent respectively which shows low efficiency compared with SEDIMENT RATING CURVEs. The results of the application of multivariate SEDIMENT RATING CURVE in various station shows that the rate of the accuracy index of multivariate SEDIMENT RATING CURVE in the best case is belong to Glinak station with the rate of 1.12. Also the average value of the accuracy index of multivariate SEDIMENT RATING CURVE is 1.15 which is an acceptable amount to the other considered various methods.

Cites

No record.

References

No record.

Cite

APA: Copy

VARVANI, J., EBRAHIMI, N., YOSEFI, M., SHADMANI, M.R., & NIKCHE FARAHANI, SH.. (2016). A PERFORMANCE EVALUATION OF NEURO-FUZZY AND REGRESSION METHODS IN ESTIMATION OF SEDIMENT LOAD OF RIVER. WATERSHED MANAGEMENT RESEARCHES (PAJOUHESH-VA-SAZANDEGI), 28(109), 104-113. SID. https://sid.ir/paper/200579/en

Vancouver: Copy

VARVANI J., EBRAHIMI N., YOSEFI M., SHADMANI M.R., NIKCHE FARAHANI SH.. A PERFORMANCE EVALUATION OF NEURO-FUZZY AND REGRESSION METHODS IN ESTIMATION OF SEDIMENT LOAD OF RIVER. WATERSHED MANAGEMENT RESEARCHES (PAJOUHESH-VA-SAZANDEGI)[Internet]. 2016;28(109):104-113. Available from: https://sid.ir/paper/200579/en

IEEE: Copy

J. VARVANI, N. EBRAHIMI, M. YOSEFI, M.R. SHADMANI, and SH. NIKCHE FARAHANI, “A PERFORMANCE EVALUATION OF NEURO-FUZZY AND REGRESSION METHODS IN ESTIMATION OF SEDIMENT LOAD OF RIVER,” WATERSHED MANAGEMENT RESEARCHES (PAJOUHESH-VA-SAZANDEGI), vol. 28, no. 109, pp. 104–113, 2016, [Online]. Available: https://sid.ir/paper/200579/en

Related Journal Papers