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Neural Network Approach for Analyzing Seismic Data to Identify Potentially Hazardous Bridges
Joint Authors
Huang, Chuhsiung
Kerh, Tienfuan
Gunaratnam, David
Source
Mathematical Problems in Engineering
Issue
Vol. 2011, Issue 2011 (31 Dec. 2011), pp.1-15, 15 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2011-06-04
Country of Publication
Egypt
No. of Pages
15
Main Subjects
Abstract EN
Examining the effect of strong ground motions on civil engineering structures is important as it concerns public safety.
The present study initially selects twenty-one bridges with lengths over 500 m in the Formosa freeway of Taiwan and collects a series of recorded seismic data from checking stations near these bridges.
Then, three seismic parameters including focal depth, epicenter distance, and local magnitude are used as the input data sets, and a model for estimating the key seismic parameter—peak ground acceleration—for each of bridge site is developed by using the neural network approach.
This model is finally combined with a simple distribution method and a new weight-based method to estimate peak ground acceleration at each of the bridges along the freeway.
Based on the seismic design value in the current building code as the evaluation criteria, the model identifies five bridges, out of all the bridges investigated, as having the potential to be subjected to significantly higher horizontal peak ground accelerations than that recommended for design in the building code.
The method presented in this study hence provides a valuable reference for dealing with nonlinear seismic data by developing neural network model, and the approach presented is also applicable to other areas of interest around the world.
American Psychological Association (APA)
Kerh, Tienfuan& Huang, Chuhsiung& Gunaratnam, David. 2011. Neural Network Approach for Analyzing Seismic Data to Identify Potentially Hazardous Bridges. Mathematical Problems in Engineering،Vol. 2011, no. 2011, pp.1-15.
https://search.emarefa.net/detail/BIM-473643
Modern Language Association (MLA)
Kerh, Tienfuan…[et al.]. Neural Network Approach for Analyzing Seismic Data to Identify Potentially Hazardous Bridges. Mathematical Problems in Engineering No. 2011 (2011), pp.1-15.
https://search.emarefa.net/detail/BIM-473643
American Medical Association (AMA)
Kerh, Tienfuan& Huang, Chuhsiung& Gunaratnam, David. Neural Network Approach for Analyzing Seismic Data to Identify Potentially Hazardous Bridges. Mathematical Problems in Engineering. 2011. Vol. 2011, no. 2011, pp.1-15.
https://search.emarefa.net/detail/BIM-473643
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-473643