The research on structural damage identification using rough set and integrated neural network

Juelong LI, Hairui LI, Jianchun XING, Qiliang YANG

PDF(116 KB)
PDF(116 KB)
Front. Mech. Eng. ›› 2013, Vol. 8 ›› Issue (3) : 305-310. DOI: 10.1007/s11465-013-0259-5
RESEARCH ARTICLE

The research on structural damage identification using rough set and integrated neural network

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Abstract

A huge amount of information and identification accuracy in large civil engineering structural damage identification has not been addressed yet. To efficiently solve this problem, a new damage identification method based on rough set and integrated neural network is first proposed. In brief, rough set was used to reduce attributes so as to decrease spatial dimensions of data and extract effective features. And then the reduced attributes will be put into the sub-neural network. The sub-neural network can give the preliminary diagnosis from different aspects of damage. The decision fusion network will give the final damage identification results. The identification examples show that this method can simplify the redundant information to reduce the neural network model, making full use of the range of information to effectively improve the accuracy of structural damage identification.

Keywords

rough set / integrated neural network / damage identification / decision making fusion

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Juelong LI, Hairui LI, Jianchun XING, Qiliang YANG. The research on structural damage identification using rough set and integrated neural network. Front Mech Eng, 2013, 8(3): 305‒310 https://doi.org/10.1007/s11465-013-0259-5

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2014 Higher Education Press and Springer-Verlag Berlin Heidelberg
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