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

Shaohong Li and Na Wu

Chaos, Solitons & Fractals, 2021, vol. 147, issue C

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.

Keywords: Grey prediction model; Hausdorff derivative; Twin support vector regression; Improved salp swarm algorithm; Landslide displacement prediction (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:147:y:2021:i:c:s0960077921003234

DOI: 10.1016/j.chaos.2021.110969

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