|Table of Contents|

Predition of Concrete Strength of Existing Buildings Based on BP Neural Networks(PDF)

《建筑科学与工程学报》[ISSN:1673-2049/CN:61-1442/TU]

Issue:
2011年01期
Page:
70-75
Research Field:
Publishing date:
2011-03-20

Info

Title:
Predition of Concrete Strength of Existing Buildings Based on BP Neural Networks
Author(s):
YOU Jie;  CHE Yi;  ZHONG Wei-qiu
YOU Jie, CHE Yi, ZHONG Wei-qiu
Keywords:
BP neural network;  existing building;  concrete strength;  momentum method;  adaptive adjustment method
PACS:
TU375
DOI:
-
Abstract:
Based on the test data analysis method, characteristic parameters of the existing buildings, i.e. service time, construction time, in-situ inspection time of structure, design value of concrete strength, and carbonation depth of concrete were extracted, and the artificial neural network model was developed to predict the degradation of concrete strength of the existing buildings. The back propagation(BP)algorithm was improved by using the momentum method and adaptive adjustment method. Both minimum and maximum values of concrete strength were predicted using the trained BP neural network and were compared with the measured values. Results show that using BP neural network to predict the degradation of concrete strength of existing buildings is feasible. Results of this study can provide references for the existing building seismic performances of large area surveys.

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Last Update: 2011-03-20