Research on displacement prediction of step-type landslide under the influence of various environmental factors based on intelligent WCA-ELM in the Three Gorges Reservoir area

Yong-gang Zhang, Xin-quan Chen, Rao-ping Liao (), Jun-li Wan, Zheng-ying He, Zi-xin Zhao, Yan Zhang and Zheng-yang Su
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Yong-gang Zhang: Tongji University
Xin-quan Chen: Xiamen Anneng Construction Co., Ltd.
Rao-ping Liao: Tongji University
Jun-li Wan: China Academy of Railway Science Co., Ltd.
Zheng-ying He: Tongji University
Zi-xin Zhao: Tongji University
Yan Zhang: Hohai University
Zheng-yang Su: Nanjing Hydraulic Research Institute

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2021, vol. 107, issue 2, No 34, 1709-1729

Abstract: Abstract Landslides are one of the most destructive geological disasters and have been caused many casualties and economic losses every year in the world. The reservoir area formed by the world's largest hydropower project, Three Gorges Hydropower project of China, has become a natural testing ground for landslide prediction in the hope of reducing losses. In this paper, a new algorithm with strong optimization ability, the water cycle algorithm (WCA), is combined with the extreme learning machine (ELM) to improve the prediction accuracy of step-wise landslide. The gray relational grade analysis method was adopted to determine the main influencing factors of the landslide's periodic displacement. Then, the determined factors were used as the input items of the proposed WCA-ELM model, and the corresponding periodic displacement was used as the model output item. Taking the Liujiabao landslide in the Three Gorges Reservoir area as a case history, the proposed model was verified through a comparison with the measurements. The results showed that the model has a faster convergence rate and higher prediction accuracy than the traditional back-propagation neural network model and ELM-model. The water cycle algorithm is suitable for optimizing the accuracy of the extreme learning machine model in landslide prediction.

Keywords: Step-type landslide; Displacement prediction; The Three Gorges Reservoir area; Intelligent water cycle algorithm; Extreme learning machine (search for similar items in EconPapers)
Date: 2021
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DOI: 10.1007/s11069-021-04655-3

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