Proceedings of the 2024 6th International Conference on Civil Engineering, Environment Resources and Energy Materials (CCESEM 2024)

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Research on High Slope Deformation Prediction Model based on ARIMA-GRNN

Authors
Qingda Duan1, *, Hua Xia1
1College of Forestry, Xinyang Agriculture and Forestry University, Xinyang, 464000, China
*Corresponding author. Email: duanqingda@126.com
Corresponding Author
Qingda Duan
Available Online 24 December 2024.
DOI
10.2991/978-94-6463-606-2_11How to use a DOI?
Keywords
high slopes; ARIMA model; GRNN neural network; prediction
Abstract

In this paper, an autoregressive integral sliding average model (ARIMA) and generalized regression neural network (GRNN) coupled high slope deformation prediction model is proposed, which mainly utilizes the long-term trend fitting ability of the ARIMA model and the short-term data prediction ability of the GRNN to significantly improve the overall prediction performance of the model. The feasibility and effectiveness of the model in practical applications are verified by comparing it with a variety of prediction models. The results show that the ARIMA-GRNN model based on residual correction is better than the traditional model in all assessment indexes, and can provide more accurate and stable prediction of high slope deformation, which provides an important decision support for the fields of geologic disaster management, environmental protection and civil engineering design, and has significant theoretical significance and practical application value.

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 6th International Conference on Civil Engineering, Environment Resources and Energy Materials (CCESEM 2024)
Series
Advances in Engineering Research
Publication Date
24 December 2024
ISBN
978-94-6463-606-2
ISSN
2352-5401
DOI
10.2991/978-94-6463-606-2_11How 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  - Qingda Duan
AU  - Hua Xia
PY  - 2024
DA  - 2024/12/24
TI  - Research on High Slope Deformation Prediction Model based on ARIMA-GRNN
BT  - Proceedings of the 2024 6th International Conference on Civil Engineering, Environment Resources and Energy Materials (CCESEM 2024)
PB  - Atlantis Press
SP  - 97
EP  - 104
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-606-2_11
DO  - 10.2991/978-94-6463-606-2_11
ID  - Duan2024
ER  -