Improved similarity assessment and spectral clustering for unsupervised linking of data extracted from bridge inspection reports-Reference-Cited by-同舟云学术

Improved similarity assessment and spectral clustering for unsupervised linking of data extracted from bridge inspection reports

Published:2022-01 Issue: Volume:51 Page:101496
ISSN:1474-0346
Container-title:Advanced Engineering Informatics
language:en
Short-container-title:Advanced Engineering Informatics

Author:

Liu Kaijian,El-Gohary Nora

Publisher

Elsevier BV

Subject

Artificial Intelligence,Information Systems,Building and Construction

Reference107 articles.

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2. FHWA (Federal Highway Administration), 2020. “Long-term bridge performance”. (Aug. 20, 2020).

3. Long-term bridge performance committee letter report: February 23, 2016;NASEM (National Academies of Sciences, Engineering, and Medicine),2015

4. FHWA (Federal Highway Administration), 2016. “The LTBP deterioration modeling algorithm - An innovative approach to accurate deterioration modeling.” (Oct. 18, 2019).

5. Xgboost application on bridge management systems for proactive damage estimation;Lim;Adv. Eng. Inform.,2019

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