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作者:

Li, Bo (Li, Bo.) | Ma, Donghui (Ma, Donghui.) (学者:马东辉) | Su, Jingyu (Su, Jingyu.) (学者:苏经宇) | Wang, Wei (Wang, Wei.) (学者:王伟)

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摘要:

The surface rupture triggered by strong earthquakes will extensively damage buildings on the ground. It is significant for choosing construction sites to forecast accurately and calculate reasonable building lien distance. The paper proposed a method which aimed to forecast the surface rupture width under strong earthquake based on information diffusion methodology. Firstly, magnitude and the thickness of overburden soil were taken as main evaluation indexes, and then fuzzy relation between two evaluation indexes and surface rupture zone width was established based on the information diffusion principle and fuzzy approximate deduction. Secondly, cross validation was used to evaluate the model's stability and accuracy, then followed by a comparation with the multiple linear regression model, quadratic regression model and BP neural network model. The results show that information diffusion methodology can deal with nonlinear relationship of every index. Finally, the validity and feasibility were proved by instance analysis.

关键词:

Neural networks Earthquakes Linear regression

作者机构:

  • [ 1 ] [Li, Bo]Institute of Earthquake Resistance and Disaster Reduction, Beijing University of Technology, Beijing 100124, China
  • [ 2 ] [Li, Bo]College of Civil Engineering, Beijing University of Technology, Beijing 100124, China
  • [ 3 ] [Ma, Donghui]Institute of Earthquake Resistance and Disaster Reduction, Beijing University of Technology, Beijing 100124, China
  • [ 4 ] [Ma, Donghui]College of Architecture and Urban Planning, Beijing University of Technology, Beijing 100124, China
  • [ 5 ] [Su, Jingyu]Institute of Earthquake Resistance and Disaster Reduction, Beijing University of Technology, Beijing 100124, China
  • [ 6 ] [Su, Jingyu]College of Architecture and Urban Planning, Beijing University of Technology, Beijing 100124, China
  • [ 7 ] [Wang, Wei]Institute of Earthquake Resistance and Disaster Reduction, Beijing University of Technology, Beijing 100124, China
  • [ 8 ] [Wang, Wei]College of Architecture and Urban Planning, Beijing University of Technology, Beijing 100124, China

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来源 :

Journal of Basic Science and Engineering

ISSN: 1005-0930

年份: 2014

期: 2

卷: 22

页码: 294-304

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SCOPUS被引频次: 4

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