A comparative evaluation of clustering methods and data sampling techniques in the prediction of reservoir landslide deformation state-Reference-Cited by-同舟云学术

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A comparative evaluation of clustering methods and data sampling techniques in the prediction of reservoir landslide deformation state

Published:2024-04-12 Issue: Volume: Page:1-17
ISSN:1749-9518
Container-title:Georisk: Assessment and Management of Risk for Engineered Systems and Geohazards
language:en
Short-container-title:Georisk: Assessment and Management of Risk for Engineered Systems and Geohazards

Author:

Ge Qi¹,Liu Zhongqiang²,Wang Xiaohong³,Wang Xu⁴,Sun Hong Yue⁴

Affiliation:

1. College of Civil Engineering, Nanjing Forestry University

2. Department of Natural Hazards, Norwegian Geotechnical Institute

3. Powerchina Huadong Engineering Corporation

4. Ocean College, Zhejiang University

Funder

the natural science foundation of jiangsu province

the state key program of the national natural science foundation

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/17499518.2024.2341257

Reference64 articles.

1. A New Integrated Approach for Landslide Data Balancing and Spatial Prediction Based on Generative Adversarial Networks (GAN)

2. Fast density clustering strategies based on the k-means algorithm

3. A study of the behavior of several methods for balancing machine learning training data

4. Full probabilistic geotechnical design under various design scenarios using direct Monte Carlo simulation and sample reweighting

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