Support vector machines in structural engineering: a review

Autor: Abdulkadir Çevik, Ahmet Emin Kurtoğlu, Mahmut Bilgehan, Mehmet Eren Gülşan, Hasan M. Albegmprli
Jazyk: angličtina
Rok vydání: 2015
Předmět:
Zdroj: Journal of Civil Engineering and Management, Vol 21, Iss 3 (2015)
Druh dokumentu: article
ISSN: 13923730
1392-3730
1822-3605
DOI: 10.3846/13923730.2015.1005021
Popis: Recent development in data processing systems had directed study and research of engineering towards the creation of intelligent systems to evolve models for a wide range of engineering problems. In this respect, several modeling techniques have been created to simulate various civil engineering systems. This study aims to review the studies on support vector machines (SVM) in structural engineering and investigate the usability of this machine learning based approach by providing three case studies focusing on structural engineering problems. Firstly, the concept of SVM is explained and then, the recent studies on the application of SVM in structural engineering are summarized and discussed. Next, we performed three case studies using the experimental studies provided. Applicability of SVM in structural engineering is confirmed by these case studies. The results showed that SVM is superior to various other learning techniques considering the generalization capability of produced model.
Databáze: Directory of Open Access Journals