Application of Artificial Intelligence for Bridge Deterioration Model
Joint Authors
Chen, Zhang
Wu, Yangyang
Li, Li
Sun, Lijun
Source
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-6, 6 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-10-22
Country of Publication
Egypt
No. of Pages
6
Main Subjects
Medicine
Information Technology and Computer Science
Abstract EN
The deterministic bridge deterioration model updating problem is well established in bridge management, while the traditional methods and approaches for this problem require manual intervention.
An artificial-intelligence-based approach was presented to self-updated parameters of the bridge deterioration model in this paper.
When new information and data are collected, a posterior distribution was constructed to describe the integrated result of historical information and the new gained information according to Bayesian theorem, which was used to update model parameters.
This AI-based approach is applied to the case of updating parameters of bridge deterioration model, which is the data collected from bridges of 12 districts in Shanghai from 2004 to 2013, and the results showed that it is an accurate, effective, and satisfactory approach to deal with the problem of the parameter updating without manual intervention.
American Psychological Association (APA)
Chen, Zhang& Wu, Yangyang& Li, Li& Sun, Lijun. 2015. Application of Artificial Intelligence for Bridge Deterioration Model. The Scientific World Journal،Vol. 2015, no. 2015, pp.1-6.
https://search.emarefa.net/detail/BIM-1079082
Modern Language Association (MLA)
Chen, Zhang…[et al.]. Application of Artificial Intelligence for Bridge Deterioration Model. The Scientific World Journal No. 2015 (2015), pp.1-6.
https://search.emarefa.net/detail/BIM-1079082
American Medical Association (AMA)
Chen, Zhang& Wu, Yangyang& Li, Li& Sun, Lijun. Application of Artificial Intelligence for Bridge Deterioration Model. The Scientific World Journal. 2015. Vol. 2015, no. 2015, pp.1-6.
https://search.emarefa.net/detail/BIM-1079082
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1079082