Application Comparison of Artificial Intelligence Method in Civil Engineering Monitoring
DING Yang1, ZHOU Shuangxi2, DONG Jingliang2, WANG Zhongping3, ZHENG Zhiqiu2
1 School of Architecture Engineering, Zhejiang University, Hangzhou 310058 2 School of Civil Engineering and Architecture, East China Jiaotong University, Nanchang 330013 3 School of Materials Science and Engineering, Tongji University, Shanghai 201804
Abstract: With the rapid development of computer technology, monitoring and forecasting methods in the field of civil engineering have been constantly updated. Taking the pouring process of mass concrete as the engineering background, combined with BP, GA-BP, PSO-BP, SOM, CNN, SVM and PNN, the prediction model was established. According to the measured data and prediction model, it can be concluded that the internal temperature of mass concrete increases first and then decreases within 2 days due to hydration and heat release. The error of prediction model based on SVM, PNN neural network and CNN neural network is less than 2%. The prediction error of BP network is about 10%, but the error is 5% after improvement by genetic algorithm. Combining seven kinds of artificial intelligence methods, choosing the appropriate algorithm and optimizing can provide the basis for monitoring, predicting and early warning in the field of civil engineering in the future.
1 杜德润, 仇德伦, 李爱群,等.无损检测,2004,26(8),383. 2 吴大宏, 赵人达. 四川建筑科学研究,2002, 28(3),4. 3 Albuthbahak O M, Alkhudery H H. International Journal of Civil engineering & Technology,2018,9(2),265. 4 Chen F C, Jahanshahi M R. IEEE Transactions on Industrial Electronics,2018,65(5),4392. 5 张帆, 胡伍生.东南大学学报(英文版),2013,29(4),441. 6 肖进胜, 刘恩雨, 朱力,等.光学学报, 2017(3),96. 7 Han B, Xiang T Y, Xie H B. Engineering Structures,2017,142(7),46. 8 丁杨. 河北工程大学学报(自然科学版),2016,33(2),30. 9 Hoseinian Fatemeh Sadat, Abdollahzadeh Aliakbar, Rezai Bahram. Journal of Central South University,2018,25(1),151. 10 戴隆州, 吴永明, 李少波,等.计算机应用研究,2018,35(1),145. 11 丁杨, 陈希杰, 杜欣,等.安徽理工大学学报(自然科学版),2017,37(4),32. 12 Deng F, He Y, Zhou S, et al. Construction and Building Materials,2018,175,562. 13 张莉, 卢星凝, 陆从林,等.中国科学技术大学学报,2017(1),1. 14 王彦富, 李玉莲, 张彪,等.安全与环境学报,2016,16(5),66. 15 翟社平, 郭琳, 高山,等.小型微型计算机系统,2018,39(5),995.
渝公网安备50019002502923号 版权所有：《材料导报》编辑部
2019, Vol. 33 
