Time Series Prediction Model of Concrete Corrosion in Sulfuric Based on SVM

被引:1
作者
Gao, Yang [1 ]
Song, Zhigang [1 ]
机构
[1] Kunming Univ Sci & Technol, Fac Civil Engn, Kunming, Peoples R China
来源
2013 INTERNATIONAL CONFERENCE ON COMPUTER SCIENCES AND APPLICATIONS (CSA) | 2013年
关键词
Time serious; support vector machine; concrete; sulfuric; prediction model;
D O I
10.1109/CSA.2013.136
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
In this paper, a long-team immersion of concrete in dilute sulfuric acid is carried out. On the basis of the experimental data, a time serious prediction model of concrete corrosion in sulfuric based on support vector machine (SVM) is developed. The design steps and learning algorithm are also given. Comparing with the test result, this model has good predictive function, with the suitable reconstructed space matrix and prediction step length. Using the latter 20 groups of test data which data spaces are reconstructed as the prediction set, most of the prediction relative error(Er) can be controlled within 15%, and only a small amount are within 30%. It implies that this model can be a new powerful way for study of concrete corrosion resistance.
引用
收藏
页码:560 / 563
页数:4
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