Estimates of bridge girder conditions based on fuzzy inspection data

Nang-Fei Pan, Huaitien Wang, Ming Der Yang, Kai Chun Hsu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

An effective bridge maintenance system requires an accurate bridge prediction model. Ordinary regression models have been extensively used to forecast future infrastructure conditions. However, data on current bridge conditions obtained from inspectors are inherently subjective and non-crisp; thus ordinary regression techniques are incapable of predicting bridge states when inspection data are fuzzy. This paper utilizes Chang's fuzzy linear regression model for the estimation of bridge girder conditions. The model can deal with a mixture of fuzzy data and crisp data. An empirical case study is used to examine the variables contributing to deterioration of bridge girders. The results demonstrate the capability of the model.

Original languageEnglish
Title of host publicationProceedings - 5th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2008
Pages537-540
Number of pages4
Volume3
DOIs
Publication statusPublished - 2008
Event5th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2008 - Jinan, Shandong, China
Duration: 2008 Oct 182008 Oct 20

Other

Other5th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2008
CountryChina
CityJinan, Shandong
Period08-10-1808-10-20

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Control and Systems Engineering

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    Pan, N-F., Wang, H., Yang, M. D., & Hsu, K. C. (2008). Estimates of bridge girder conditions based on fuzzy inspection data. In Proceedings - 5th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2008 (Vol. 3, pp. 537-540). [4666303] https://doi.org/10.1109/FSKD.2008.655