Machine Learning for Risk and Resilience Assessment in Structural Engineering: Progress and Future Trends-Reference-Cited by-同舟云学术

Machine Learning for Risk and Resilience Assessment in Structural Engineering: Progress and Future Trends

Author:

Wang Xiaowei¹^ORCID,Mazumder Ram K.²^ORCID,Salarieh Babak³^ORCID,Salman Abdullahi M.⁴^ORCID,Shafieezadeh Abdollah⁵^ORCID,Li Yue⁶

Affiliation:

1. Associate Professor, Dept. of Bridge Engineering, Tongji Univ., Shanghai 200092, China (corresponding author). ORCID: .

2. Postdoctoral Researcher, Dept. of Civil, Environmental and Architectural Engineering, Univ. of Kansas, Lawrence, KS 66045. ORCID: .

3. Ph.D. Candidate, Dept. of Civil and Environmental Engineering, Univ. of Alabama in Huntsville, Huntsville, AL 35899. ORCID: .

4. Assistant Professor, Dept. of Civil and Environmental Engineering, Univ. of Alabama in Huntsville, Huntsville, AL 35899. ORCID: .

5. Lichtenstein Associate Professor, Dept. of Civil, Environmental and Geodetic Engineering, Ohio State Univ., Columbus, OH 43210. ORCID: .

6. Leonard Case Jr. Professor in Engineering, Dept. of Civil and Environmental Engineering, Case Western Reserve Univ., Cleveland, OH 44106.

Publisher

American Society of Civil Engineers (ASCE)

Subject

Mechanical Engineering,Mechanics of Materials,General Materials Science,Building and Construction,Civil and Structural Engineering

Link

Reference260 articles.

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