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Bulletin of Engineering Geology and the Environment

Erschienen in:

01.05.2016 | Original Paper

Prediction of landslide displacement based on GA-LSSVM with multiple factors

verfasst von: Zhenglong Cai, Weiya Xu, Yongdong Meng, Chong Shi, Rubin Wang

Erschienen in: Bulletin of Engineering Geology and the Environment | Ausgabe 2/2016

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Abstract

This paper presents a new model for predicting the displacement of a landslide based on the least-squares support vector machine (LSSVM) with multiple factors and a genetic algorithm (GA) is used to optimize the parameters of the LSSVM model. First, based on original monitoring displacement data, single factor GA-LSSVM models are established with and without wavelet decomposition. Second, from the analysis of the basic characteristics of a landslide, the main influencing factors of landslide displacement are identified according to their correlation coefficients. A multifactor GA-LSSVM model is then established for the prediction of landslide displacement. A case study of a landslide reveals that wavelet decomposition can efficiently improve the prediction accuracy of the GA-LSSVM model. In addition, the multifactor GA-LSSVM model performs consistently better than the single factor models for the same measurements.

Vorheriger Artikel Predisposing factors and the mechanisms of rainfall-induced slope movements in Ugwueme, South-East Nigeria

Nächster Artikel Back analysis of a debris landslide based on a real-time video recording: sliding process and post-slide investigation

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Titel: Prediction of landslide displacement based on GA-LSSVM with multiple factors
verfasst von: Zhenglong Cai
Weiya Xu
Yongdong Meng
Chong Shi
Rubin Wang
Publikationsdatum: 01.05.2016
Verlag: Springer Berlin Heidelberg
Erschienen in: Bulletin of Engineering Geology and the Environment / Ausgabe 2/2016
Print ISSN: 1435-9529
Elektronische ISSN: 1435-9537
DOI: https://doi.org/10.1007/s10064-015-0804-z

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