Multi-objective optimisation of in-service asphalt pavement maintenance schedule considering system reliability estimated via LSTM neural networks-Reference-Cited by-同舟云学术

Multi-objective optimisation of in-service asphalt pavement maintenance schedule considering system reliability estimated via LSTM neural networks

Published:2022-02-25 Issue:7 Volume:18 Page:1002-1019
ISSN:1573-2479
Container-title:Structure and Infrastructure Engineering
language:en
Short-container-title:Structure and Infrastructure Engineering

Author:

Xin Jiyu¹^ORCID,Akiyama Mitsuyoshi¹^ORCID,Frangopol Dan M.²^ORCID,Zhang Mingyang³^ORCID

Affiliation:

1. Department of Civil and Environmental Engineering, Waseda University, Tokyo, Japan

2. Department of Civil and Environmental Engineering, Engineering Research Center for Advanced Technology for Large Structural Systems (ATLSS Center), Lehigh University, Bethlehem, PA, USA

3. Department of Bridge Engineering, Tongji University, Shanghai, China

Funder

China Scholarship Council (CSC) under the CSC-WASEDA Joint Scholarship Program

Promotion of Science

research of the first author at Waseda University and Shanghai Sailing Program

Publisher

Informa UK Limited

Subject

Mechanical Engineering,Ocean Engineering,Geotechnical Engineering and Engineering Geology,Safety, Risk, Reliability and Quality,Building and Construction,Civil and Structural Engineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/15732479.2022.2038641

Reference82 articles.

1. A New Method of Interpolation and Smooth Curve Fitting Based on Local Procedures

2. Toward life-cycle reliability-, risk- and resilience-based design and assessment of bridges and bridge networks under independent and interacting hazards: emphasis on earthquake, tsunami and corrosion

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