ASSESSMENT OF DATA-MINING AND SOME EMPIRICAL METHODS IN SCOUR DEPTH ESTIMATION AT BRICLGE PIERS

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.

SATTARI MOHAMMAD TAGHI; REZAZADEH JOUDI ALI; ARVANAGHI HADI

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

Journal Paper

Paper Information

Journal: Journal of Water Resources Engineering Year:2016 | Volume:9 | Issue:30 Page(s): 25-36

Download Full-Text

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

Persian Verion

View:

819

Download:

Cites:

Information Journal Paper

Title

ASSESSMENT OF DATA-MINING AND SOME EMPIRICAL METHODS IN SCOUR DEPTH ESTIMATION AT BRICLGE PIERS

Author(s)

SATTARI MOHAMMAD TAGHI | REZAZADEH JOUDI ALI | ARVANAGHI HADI | Issue Writer Certificate

Keywords

LOCAL SCOURQ1

DATA MININGQ2

M5 MODEL TREEQ1

ARTIFICIAL NEURAL NETWORKSQ1

EMPIRICAL EQUATIONSQ1

Abstract

LOCAL SCOUR at. bridge pieds is one of the numeroussafty hazaraels that the eaten their stability. An abundance of such facfors and their complexities, along with a mulfiplicity of empirical relationships, make the development of an integrated approach for estimation of scour depth very difficult. However, the presence of novel data-mining approaches such as the artificial nevral networks (ANN) and the M5 Tree Model has facilitated the solution of complicated engineering problems. In this study by using laboratory data and identifying 10 scenarios including different combinations of effective parameters in scour depth, the performance of ANN and M5 tree models have been investigated and results compared with 3 empirical relationships (Melville, Mississippi and HEC-18). The results indicated that the M5 Tree Model via presenting 2 simple if-then rules and may CC=0.95 in comparison with the other ANN and empirical approaches may estimate scour depth with high accuracy. The results ahso indicated that between the 3 used empirical relations, HEC-18, Mississippi and Melville relations presents high accuracy, respecfively.

Cites

No record.

References

Cite

APA: Copy

SATTARI, MOHAMMAD TAGHI, REZAZADEH JOUDI, ALI, & ARVANAGHI, HADI. (2016). ASSESSMENT OF DATA-MINING AND SOME EMPIRICAL METHODS IN SCOUR DEPTH ESTIMATION AT BRICLGE PIERS. WATER ENGINEERING, 9(30), 25-36. SID. https://sid.ir/paper/169367/en

Vancouver: Copy

SATTARI MOHAMMAD TAGHI, REZAZADEH JOUDI ALI, ARVANAGHI HADI. ASSESSMENT OF DATA-MINING AND SOME EMPIRICAL METHODS IN SCOUR DEPTH ESTIMATION AT BRICLGE PIERS. WATER ENGINEERING[Internet]. 2016;9(30):25-36. Available from: https://sid.ir/paper/169367/en

IEEE: Copy

MOHAMMAD TAGHI SATTARI, ALI REZAZADEH JOUDI, and HADI ARVANAGHI, “ASSESSMENT OF DATA-MINING AND SOME EMPIRICAL METHODS IN SCOUR DEPTH ESTIMATION AT BRICLGE PIERS,” WATER ENGINEERING, vol. 9, no. 30, pp. 25–36, 2016, [Online]. Available: https://sid.ir/paper/169367/en

Related Journal Papers