The Prediction for Concrete Carbonation Depth Based on RBF Neural Network

摘要：

Concrete carbonation is affected by many uncertainty factors. RBF neural network has the advantage of adaptive certainty and the output value has nothing to do with the initial weights. According to the main factors affecting concrete carbonation, prediction model for concrete carbonation depth is established based on the advantages of RBF neural network. Combining with the MATLAB mathematical software, it is used to test mathematical model by the experimental data. The prediction of results show that the forecast results conform to the test results very well. It can prove that can be considered a reasonable method.

关键词： concrete concrete carbonation depth RBF neural network MATLAB

作者: Gu Zhixiang Zhang Bin

作者单位: LiaoNing Technical University, Institute of Civil Engineering and Transportation Liao Ning Fu Xin China

会议类型: 国际会议

会议名称: 2010 International Conference on Information Security and Artificial Intelligence(2010年信息安全与人工智能国际会议 ISAI 2010)

会议地点: 成都

会议语种:英文

页码: 1005-1008

在线出版日期: 2010-12-17（万方平台首次上网日期，不代表论文的发表时间）