Predicting Crack Width of Reinforced Concrete Beams by Artificial Neural Networks

被引：0

作者：

Yan, Lei-yuan ^{[1
]}

Xie, Chao-peng ^{[1
]}

Feng, Fan ^{[2
]}

Liu, Gui-rong ^{[1
]}

Guan, Jun-feng ^{[1
]}

Ning, Yu ^{[1
]}

Chen, Dian-xiang ^{[1
]}

机构：

[1] North China Univ Water Resources & Elect Power, Zhengzhou, Peoples R China

[2] MWR, Ctr Construct Management & Qual & Safety Supervis, Beijing 100038, Peoples R China

来源：

3RD INTERNATIONAL CONFERENCE ON CIVIL ENGINEERING, ARCHITECTURE AND SUSTAINABLE INFRASTRUCTURE, ICCEASI 2015 | 2015年

关键词：

D O I：

暂无

中图分类号：

TU [建筑科学];

学科分类号：

0813 ;

摘要：

A method for predicting the crack width of reinforced concrete beam was proposed in this paper. Based on the test results, a three-layer back-propagation network is trained using the experimental data, among which 237 groups are used for training sample while the remaining 9 groups are used for testing sample. The crack widths of reinforced concrete flexural members were predicted by artificial neural network (ANN). Results show that the predicted results agree well with the test data. Thus, ANN method can estimate crack width of reinforced concrete flexural members in practice.

引用

页码：608 / 613

页数：6

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