Metaheuristic-based support vector regression for landslide displacement prediction: a comparative study

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Location: Deutsche Nationalbibliothek Frankfurt am Main

ISSN: 1612-5118

Extent: Online-Ressource

Language: Englisch

Notes: online resource.

Bibliographic citation: Metaheuristic-based support vector regression for landslide displacement prediction: a comparative study ; day:30 ; month:6 ; year:2022 ; pages:1-23
Landslides ; (30.6.2022), 1-23

Creator: Ma, Junwei
Xia, Ding
Guo, Haixiang
Wang, Yankun
Niu, Xiaoxu
Liu, Zhiyang
Jiang, Sheng

Contributor: SpringerLink (Online service)

DOI: 10.1007/s10346-022-01923-6

URN: urn:nbn:de:101:1-2022082106030230996418

Rights: Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.

Last update: 15.08.2025, 7:28 AM CEST

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Ma, Junwei
Xia, Ding
Guo, Haixiang
Wang, Yankun
Niu, Xiaoxu
Liu, Zhiyang
Jiang, Sheng
SpringerLink (Online service)

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Metaheuristic-based support vector regression for landslide displacement prediction: a comparative study

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Other Objects (12)

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Metaheuristic clustering

Analysing metaheuristic components

Regression depth and support vector machine

Regression Depth and Support Vector Machine

Landslide displacement forecasting using deep learning and monitoring data across selected sites

Simultaneous state–parameter estimation of rainfall-induced landslide displacement using data assimilation

Research and application of flexible measuring array for deep displacement of landslide

Dense 3D displacement vector fields for point cloud-based landslide monitoring

Displacement residuals reveal landslide regime shifts

Vector quantile regression

Vector regression introduced

Optimization of SVR and CatBoost models using metaheuristic algorithms to assess landslide susceptibility

Metaheuristic clustering

Analysing metaheuristic components

Regression depth and support vector machine

Regression Depth and Support Vector Machine

Landslide displacement forecasting using deep learning and monitoring data across selected sites

Simultaneous state–parameter estimation of rainfall-induced landslide displacement using data assimilation

Research and application of flexible measuring array for deep displacement of landslide

Dense 3D displacement vector fields for point cloud-based landslide monitoring

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Vector quantile regression

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Optimization of SVR and CatBoost models using metaheuristic algorithms to assess landslide susceptibility

Metaheuristic clustering

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Regression depth and support vector machine

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Landslide displacement forecasting using deep learning and monitoring data across selected sites

Simultaneous state–parameter estimation of rainfall-induced landslide displacement using data assimilation

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