Study on the RBF landslide prediction model based on the Grey-Markov theory of time series

Lixin Peng; Bo Wu; Xin Zhang; Junjie Li

doi:10.1117/12.3028958

22 May 2024 Study on the RBF landslide prediction model based on the Grey-Markov theory of time series

Lixin Peng, Bo Wu, Xin Zhang, Junjie Li

Proceedings Volume 13176, Fourth International Conference on Machine Learning and Computer Application (ICMLCA 2023); 131762L (2024) https://doi.org/10.1117/12.3028958
Event: Fourth International Conference on Machine Learning and Computer Application (ICMLCA 2023), 2023, Hangzhou, China

Abstract

The accurate prediction of landslide displacement is an important part of social stability and plays an important role in economic development. Therefore, it is a very important topic for how to accurately predict the changes in landslide displacement. According to the research of previous scholars, this paper proposes a multi-model analysis and prediction method that combines gray system preprocessing, radial basis function neural network model, and Markov chain state matrix to predict and modify landslide displacement. Compared with the single RBF model, RMSE and MAPE can be increased to 449.8mm and 0.38%. Grey-PSO-RBF model RMSE and MAPE respectively 437.5mm and 0.33%.No difference between Grey-Markov-RBF and Grey-PSO-RBF.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Lixin Peng, Bo Wu, Xin Zhang, and Junjie Li "Study on the RBF landslide prediction model based on the Grey-Markov theory of time series", Proc. SPIE 13176, Fourth International Conference on Machine Learning and Computer Application (ICMLCA 2023), 131762L (22 May 2024); https://doi.org/10.1117/12.3028958

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