Quantification of Fatigue Damage for Structural Details in Slender Coastal Bridges Using Machine Learning-Based Methods

Author:

Lu Qin1,Zhu Jin2ORCID,Zhang Wei3ORCID

Affiliation:

1. Graduate Student, Dept. of Civil and Environmental Engineering, Univ. of Connecticut, Storrs, CT 06269.

2. Assistant Professor, Dept. of Bridge Engineering, Southwest Jiaotong Univ., Chengdu 611756, China. ORCID: .

3. Assistant Professor, Dept. of Civil and Environmental Engineering, Univ. of Connecticut, Storrs, CT 06269 (corresponding author). ORCID: .

Publisher

American Society of Civil Engineers (ASCE)

Subject

Building and Construction,Civil and Structural Engineering

Reference56 articles.

1. Improving support vector machine classifiers by modifying kernel functions;Amari S.;Neural Networks,1999

2. An introduction to support vector machines and other kernel-based learning methods;Andrew A. M.;Kybernetes,2001

3. A multi-objective artificial immune algorithm for parameter optimization in support vector machine;Aydin I.;Appl. Soft Comput.,2011

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