Prediction of welding shrinkage deformation of bridge steel box girder based on Wavelet Neural Network

DOI

10.2991/amcce-18.2018.75How to use a DOI?

Keywords

Bridge Steel Box Girder, Wavelet Neural Network, Prediction Method

Abstract

Aiming at the low accuracy of traditional forecasting methods such as linear regression method, this paper presents a prediction method for predicting the relationship between bridge steel box girder and its displacement with wavelet neural network. Compared with traditional forecasting methods, this scheme has better local characteristics and learning ability, which greatly improves the prediction ability of deformation. Through analysis of the instance and found that after compared with the traditional prediction method based on wavelet neural network, the rigid beam deformation prediction accuracy is higher, and is superior to the BP neural network prediction results, conform to the actual demand of engineering design.

Copyright

© 2018, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Yulong Tao
AU  - Yunshui Miao
AU  - Jiaqi Han
AU  - Feiyun Yan
PY  - 2018/05
DA  - 2018/05
TI  - Prediction of welding shrinkage deformation of bridge steel box girder based on Wavelet Neural Network
BT  - Proceedings of the 2018 3rd International Conference on Automation, Mechanical Control and Computational Engineering (AMCCE 2018)
PB  - Atlantis Press
SP  - 440
EP  - 444
SN  - 2352-5401
UR  - https://doi.org/10.2991/amcce-18.2018.75
DO  - 10.2991/amcce-18.2018.75
ID  - Tao2018/05
ER  -