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A new grey prediction model and its application in landslide displacement prediction

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  • Li, Shaohong
  • Wu, Na

Abstract

Developing a grey prediction model with high nonlinear prediction accuracy is an important issue in grey system theory. A new grey prediction model was developed that was the first to combine the idea of twin support vector regression with Hausdorff derivative operator. The new model is a non-linear data-driven model. An improved salp swarm algorithm is used to determine parameters of the model. Two numerical examples show that the error of the new model is smaller than the existing grey prediction models and least square support vector machine model. Moreover, with the displacement, precipitation, reservoir level elevation, variation velocity of reservoir level elevation, and displacement velocity of the previous month as the input variables, the new model was successfully used to predict the displacement of a landslide in the real-world. The new model is a powerful tool for solving nonlinear prediction problems.

Suggested Citation

  • Li, Shaohong & Wu, Na, 2021. "A new grey prediction model and its application in landslide displacement prediction," Chaos, Solitons & Fractals, Elsevier, vol. 147(C).
  • Handle: RePEc:eee:chsofr:v:147:y:2021:i:c:s0960077921003234
    DOI: 10.1016/j.chaos.2021.110969
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    References listed on IDEAS

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    1. Chen, Yan & Lifeng, Wu & Lianyi, Liu & Kai, Zhang, 2020. "Fractional Hausdorff grey model and its properties," Chaos, Solitons & Fractals, Elsevier, vol. 138(C).
    2. Xiuzhen Li & Jiming Kong & Zhenyu Wang, 2012. "Landslide displacement prediction based on combining method with optimal weight," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 61(2), pages 635-646, March.
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    Cited by:

    1. Zian Lin & Yuanfa Ji & Weibin Liang & Xiyan Sun, 2022. "Landslide Displacement Prediction Based on Time-Frequency Analysis and LMD-BiLSTM Model," Mathematics, MDPI, vol. 10(13), pages 1-19, June.
    2. Zian Lin & Yuanfa Ji & Xiyan Sun, 2023. "Landslide Displacement Prediction Based on CEEMDAN Method and CNN–BiLSTM Model," Sustainability, MDPI, vol. 15(13), pages 1-20, June.

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