Prediction of welding shrinkage deformation of bridge steel box girder based on Wavelet Neural Network
Yulong Tao, Yunshui Miao, Jiaqi Han, Feiyun Yan
Available Online May 2018.
- https://doi.org/10.2991/amcce-18.2018.75How to use a DOI?
- Bridge Steel Box Girder, Wavelet Neural Network, Prediction Method
- 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.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
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 - 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 - https://doi.org/10.2991/amcce-18.2018.75 ID - Tao2018/05 ER -