MODELING THE PATCH LOAD RESISTANCE OF PLATE GIRDERS USING A SUPPORT VECTOR MACHINE

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.

KORDJAZI A.R.; POOYA NEJAD F.; SHAHABIAN F.

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

Journal Paper

Paper Information

Journal: Ferdowsi Civil Engineering Year:2017 | Volume:28 | Issue:2 (16) Page(s): 109-123

Download Full-Text

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

Persian Verion

View:

1,082

Download:

Cites:

Information Journal Paper

Title

MODELING THE PATCH LOAD RESISTANCE OF PLATE GIRDERS USING A SUPPORT VECTOR MACHINE

Author(s)

KORDJAZI A.R. | POOYA NEJAD F. | SHAHABIAN F. | Issue Writer Certificate

Keywords

PLATE GIRDERSQ2

PATCH LOADINGQ2

SUPPORT VECTOR MACHINEQ1

Abstract

The SUPPORT VECTOR MACHINE (SVM) is a relatively new machine learning method which is increasingly being applied to engineering problems and have yielded encouraging results. Because of complex behavior of elastoplastic of web panels of PLATE GIRDERS under PATCH LOADING, almost none of the proposed methods provides consistent and accurate predictions of patch load capacity. Consequently, alternative solutions are required to overcome these limitations. In this paper SVM models are developed for predicting the ultimate resistance of PLATE GIRDERS subjected to PATCH LOADING. The training and testing patterns of the proposed SVM models are based on well established experimental results taken from literature. Finally a comparison is made between predictions obtained from the SVM models and a traditional method for determining PATCH LOADING resistance. The comparison confirms that the SVM models developed in this paper, outperform the traditional method.

Cites

No record.

References

A NEURAL NETWORK EVALUATION OF THE ULTIMATE RESISTANCE OF PLATE GIRDERS SUBJECTED TO PATCH LOADING (TECHNICAL NOTE)

Cite

APA: Copy

KORDJAZI, A.R., POOYA NEJAD, F., & SHAHABIAN, F.. (2017). MODELING THE PATCH LOAD RESISTANCE OF PLATE GIRDERS USING A SUPPORT VECTOR MACHINE. JOURNAL OF CIVIL ENGINEERING (JOURNAL OF SCHOOL OF ENGINEERING), 28(2 (16)), 109-123. SID. https://sid.ir/paper/195929/en

Vancouver: Copy

KORDJAZI A.R., POOYA NEJAD F., SHAHABIAN F.. MODELING THE PATCH LOAD RESISTANCE OF PLATE GIRDERS USING A SUPPORT VECTOR MACHINE. JOURNAL OF CIVIL ENGINEERING (JOURNAL OF SCHOOL OF ENGINEERING)[Internet]. 2017;28(2 (16)):109-123. Available from: https://sid.ir/paper/195929/en

IEEE: Copy

A.R. KORDJAZI, F. POOYA NEJAD, and F. SHAHABIAN, “MODELING THE PATCH LOAD RESISTANCE OF PLATE GIRDERS USING A SUPPORT VECTOR MACHINE,” JOURNAL OF CIVIL ENGINEERING (JOURNAL OF SCHOOL OF ENGINEERING), vol. 28, no. 2 (16), pp. 109–123, 2017, [Online]. Available: https://sid.ir/paper/195929/en

Related Journal Papers