[1]XU Junzu,CAO Yanbo,LI Li,et al.Research on the Earthquake-damage Assessment of Masonry-timber Houses in Yunnan by Integrating the Principal Component Analysis with the BP Neural Network[J].Journal of Seismological Research,2023,46(03):430-439.[doi:10.20015/j.cnki.ISSN1000-0666.2023.0058
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Research on the Earthquake-damage Assessment of Masonry-timber Houses in Yunnan by Integrating the Principal Component Analysis with the BP Neural Network
Journal of Seismological Research[ISSN 1000-0666/CN 53-1062/P] Volume:
46
Number of periods:
2023 03
Page number:
430-439
Column:
Public date:
2023-06-25
- Title:
- Research on the Earthquake-damage Assessment of Masonry-timber Houses in Yunnan by Integrating the Principal Component Analysis with the BP Neural Network
- Keywords:
- the principal component analysis; the neural network model; masonry-timber structure; earthquake-damage assessment; Yunnan
- CLC:
- P315.94
- DOI:
- 10.20015/j.cnki.ISSN1000-0666.2023.0058
- Abstract:
- There are a lot of factors affecting the earthquake damage to brick-timber houses,and selecting appropriate influencing factors is an important guarantee for an accurate and reasonable assessment of the earthquake damage to masonry-timber houses. The question is that when using the traditional methods,it is difficult to choose proper factors. In this paper,a method for assessing the earthquake damage to masonry-timber houses in Yunnan is proposed by integrating the principal component analysis and the neural network. Firstly,the less-influencing factors are eliminated through the gray correlation degree model and the key factors are obtained. Secondly,the main components from the key factors are extracted through the principal component analysis.Finally,the main components are trained through the BP neural network model,and a pre-estimating model for the earthquake-damage ratio of masonry-limber houses is established. This method is tested by using the data from the post-earthquake investigation of some historical earthquakes,and the results show that this method is more accurate and applicable for pre-estimating the earthquake damage ratio of masonry-timber houses than the traditional vulnerability curve fitting and the neural network model.
- References:
- -
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Last Update:
2023-06-25