Proceedings of the 2024 3rd International Conference on Structural Seismic Resistance, Monitoring and Detection (SSRMD 2024)

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Multi-scale combined prediction model of concrete dam deformation based on VMD-LSTM-ARIMA

Authors
Tao Zhang1, *, Huaizhi Su2
1PowerChina Huadong Engineering Corporation Limited, Hangzhou, 311122, China
2College of Water Conservancy and Hydropower Engineering, Hohai University, Nanjing, 210098, China
*Corresponding author. Email: zhang_t29@hdec.com
Corresponding Author
Tao Zhang
Available Online 29 April 2024.
DOI
10.2991/978-94-6463-404-4_20How to use a DOI?
Keywords
Concrete dam; Deformation prediction; Variational mode decomposition; Long short-term memory network; ARIMA
Abstract

The deformation of concrete dam can be regarded as the result of the synergistic action of hydraulic component, temperature component and aging component. According to the different component characteristics of deformation and the correlation of different time scales, a multi-scale combined prediction model for concrete dam deformation based on VMD-LSTM-ARIMA is proposed. Firstly, using the adaptive analysis function of VMD, the trend term and cycle term of dam deformation are decomposed. Secondly, LSTM model is used to effectively predict the cycle term and trend term under different scales, and ARIMA model is used to identify the effective information of the remaining term. Finally, based on a practical project, the effectiveness and superiority of the proposed model are verified by comparing with the conventional combination algorithm. The calculation results show that the combined model fully considers the characteristics of the dam deformation, and can effectively fit and predict the dam deformation.

Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2024 3rd International Conference on Structural Seismic Resistance, Monitoring and Detection (SSRMD 2024)
Series
Atlantis Highlights in Engineering
Publication Date
29 April 2024
ISBN
10.2991/978-94-6463-404-4_20
ISSN
2589-4943
DOI
10.2991/978-94-6463-404-4_20How to use a DOI?
Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Tao Zhang
AU  - Huaizhi Su
PY  - 2024
DA  - 2024/04/29
TI  - Multi-scale combined prediction model of concrete dam deformation based on VMD-LSTM-ARIMA
BT  - Proceedings of the 2024 3rd International Conference on Structural Seismic Resistance, Monitoring and Detection (SSRMD 2024)
PB  - Atlantis Press
SP  - 196
EP  - 206
SN  - 2589-4943
UR  - https://doi.org/10.2991/978-94-6463-404-4_20
DO  - 10.2991/978-94-6463-404-4_20
ID  - Zhang2024
ER  -