[1] Wang Yanhua, Lü Jing, Wu Jing, Wang Cheng, et al. Prediction method of restoring force based on online AdaBoostregression tree algorithm in hybrid test [J]. Journal of Southeast University (English Edition), 2020, 36 (2): 181-187. [doi:10.3969/j.issn.1003-7985.2020.02.008]

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Prediction method of restoring force based on online AdaBoostregression tree algorithm in hybrid test()

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Journal of Southeast University (English Edition)[ISSN:1003-7985/CN:32-1325/N]

Volumn:

36

Issue:

2020 2

Page:

181-187

Research Field:

Civil Engineering

Publishing date:

2020-06-20

Info

Title:

Prediction method of restoring force based on online AdaBoostregression tree algorithm in hybrid test

Author(s):

Wang Yanhua;  Lü Jing;  Wu Jing;  Wang Cheng

Key Laboratory of Concrete and Pre-stressed Concrete Structures of Ministry of Education, Southeast University, Nanjing 210096, China

Keywords:

hybrid test;  restoring force prediction;  generalization ability;  AdaBoost regression tree

PACS:

TU352

DOI:

10.3969/j.issn.1003-7985.2020.02.008

Abstract:

In order to solve the poor generalization ability of the back-propagation(BP)neural network in the model updating hybrid test, a novel method called the AdaBoost regression tree algorithm is introduced into the model updating procedure in hybrid tests. During the learning phase, the regression tree is selected as a weak regression model to be trained, and then multiple trained weak regression models are integrated into a strong regression model. Finally, the training results are generated through voting by all the selected regression models. A 2-DOF nonlinear structure was numerically simulated by utilizing the online AdaBoost regression tree algorithm and the BP neural network algorithm as a contrast. The results show that the prediction accuracy of the online AdaBoost regression algorithm is 48.3% higher than that of the BP neural network algorithm, which verifies that the online AdaBoost regression tree algorithm has better generalization ability compared to the BP neural network algorithm. Furthermore, it can effectively eliminate the influence of weight initialization and improve the prediction accuracy of the restoring force in hybrid tests.

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Memo

Memo:

Biography: Wang Yanhua(1977—), female, doctor, senior engineer, wyh00737@seu.edu.cn.
Foundation item: The National Natural Science Foundation of China(No.51708110).
Citation: Wang Yanhua, Lü Jing, Wu Jing, et al.Prediction method of restoring force based on online AdaBoost regression tree algorithm in hybrid test[J].Journal of Southeast University(English Edition), 2020, 36(2):181-187.DOI:10.3969/j.issn.1003-7985.2020.02.008.

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