Structural Damage Identification Based on Rough Sets and Artificial Neural Network
Joint Authors
Liu, Chengyin
Liu, Chunyu
Wu, Xiang
Wu, Ning
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-06-11
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Medicine
Information Technology and Computer Science
Abstract EN
This paper investigates potential applications of the rough sets (RS) theory and artificial neural network (ANN) method on structural damage detection.
An information entropy based discretization algorithm in RS is applied for dimension reduction of the original damage database obtained from finite element analysis (FEA).
The proposed approach is tested with a 14-bay steel truss model for structural damage detection.
The experimental results show that the damage features can be extracted efficiently from the combined utilization of RS and ANN methods even the volume of measurement data is enormous and with uncertainties.
American Psychological Association (APA)
Liu, Chengyin& Wu, Xiang& Wu, Ning& Liu, Chunyu. 2014. Structural Damage Identification Based on Rough Sets and Artificial Neural Network. The Scientific World Journal،Vol. 2014, no. 2014, pp.1-9.
https://search.emarefa.net/detail/BIM-1048674
Modern Language Association (MLA)
Liu, Chengyin…[et al.]. Structural Damage Identification Based on Rough Sets and Artificial Neural Network. The Scientific World Journal No. 2014 (2014), pp.1-9.
https://search.emarefa.net/detail/BIM-1048674
American Medical Association (AMA)
Liu, Chengyin& Wu, Xiang& Wu, Ning& Liu, Chunyu. Structural Damage Identification Based on Rough Sets and Artificial Neural Network. The Scientific World Journal. 2014. Vol. 2014, no. 2014, pp.1-9.
https://search.emarefa.net/detail/BIM-1048674
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1048674