Input-parameter optimization using a SVR based ensemble model to predict landslide displacements in a reservoir area – A comparative study-Reference-Cited by-同舟云学术

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Input-parameter optimization using a SVR based ensemble model to predict landslide displacements in a reservoir area – A comparative study

Published:2024-01 Issue: Volume:150 Page:111107
ISSN:1568-4946
Container-title:Applied Soft Computing
language:en
Short-container-title:Applied Soft Computing

Author:

Zhang Junrong,Lin Chengyuan,Tang Huiming,Wen Tao,Tannant Dwayne D.,Zhang Bocheng

Funder

National Natural Science Foundation of China

China Postdoctoral Science Foundation

National Key Scientific Instrument and Equipment Development Projects of China

Publisher

Elsevier BV

Subject

Software

Reference54 articles.

1. Landslide data analysis using various time-series forecasting models;Aggarwal;Comput. Electr. Eng.,2020

2. Forecast modeling and performance assessment of solar PV systems;Ameur;J. Clean. Prod.,2020

3. Spatial prediction of rainfall-induced landslides for the Lao Cai area (Vietnam) using a hybrid intelligent approach of least squares support vector machines inference model and artificial bee colony optimization;Bui;Landslides,2017

4. Prediction of landslide displacement based on GA-LSSVM with multiple factors;Cai;Bull. Eng. Geol. Environ.,2016

5. Using an extreme learning machine to predict the displacement of step-like landslides in relation to controlling factors;Cao;Landslides,2016

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