An enhanced extreme learning machine model for river flow forecasting: State-of-the-art, practical applications in water resource engineering area and future research …

ZM Yaseen, SO Sulaiman, RC Deo, KW Chau - Journal of Hydrology, 2019 - Elsevier
Despite the massive diversity in the modeling requirements for practical hydrological
applications, there remains a need to develop more reliable and intelligent expert systems …

Landslide susceptibility prediction based on remote sensing images and GIS: Comparisons of supervised and unsupervised machine learning models

Z Chang, Z Du, F Zhang, F Huang, J Chen, W Li… - Remote Sensing, 2020 - mdpi.com
Landslide susceptibility prediction (LSP) has been widely and effectively implemented by
machine learning (ML) models based on remote sensing (RS) images and Geographic …

Time series analysis and long short-term memory neural network to predict landslide displacement

B Yang, K Yin, S Lacasse, Z Liu - Landslides, 2019 - Springer
A good prediction of landslide displacement is an essential component for implementing an
early warning system. In the Three Gorges Reservoir Area (TGRA), many landslides deform …

Application of an enhanced BP neural network model with water cycle algorithm on landslide prediction

Y Zhang, J Tang, R Liao, M Zhang, Y Zhang… - … Research and Risk …, 2021 - Springer
The landslide caused a huge disaster to the living environment and seriously threatened the
lives and property safety of nearby residents. Assess or predict landslide-susceptible the …

[HTML][HTML] Prediction of landslide displacement with dynamic features using intelligent approaches

Y Zhang, J Tang, Y Cheng, L Huang, F Guo… - International Journal of …, 2022 - Elsevier
Landslide displacement prediction can enhance the efficacy of landslide monitoring system,
and the prediction of the periodic displacement is particularly challenging. In the previous …

Landslide displacement prediction based on multivariate chaotic model and extreme learning machine

F Huang, J Huang, S Jiang, C Zhou - Engineering Geology, 2017 - Elsevier
This paper proposes a multivariate chaotic Extreme Learning Machine (ELM) model for the
prediction of the displacement of reservoir landslides. The displacement time series of the …

基于逻辑回归模型和3S 技术的思南县滑坡易发性评价

胡涛, 樊鑫, 王硕, 郭子正, 刘爱昌, 黄发明 - 地质科技通报, 2020 - dzkjqb.cug.edu.cn
区域滑坡易发性评价对滑坡灾害防治具有重要意义, 贵州省思南县由于其特殊的自然地理和地质
条件, 受滑坡地质灾害的影响非常严重, 因此, 非常有必要对思南县的滑坡易发性进行评价 …

Landslide displacement prediction based on variational mode decomposition and WA-GWO-BP model

Z Guo, L Chen, L Gui, J Du, K Yin, HM Do - Landslides, 2020 - Springer
Many models have been widely used in landslide displacement prediction. However, few
studies have proposed quantitative prediction formulas. Thus, the variational mode …

Prediction model oriented for landslide displacement with step-like curve by applying ensemble empirical mode decomposition and the PSO-ELM method

H Du, D Song, Z Chen, H Shu, Z Guo - Journal of Cleaner Production, 2020 - Elsevier
For landslides characterized with “step-like” deformation curves, the accelerations of the
deformation during the rainy season are destructive for both residents and infrastructure; …

Remote sensing precursors analysis for giant landslides

H Lan, X Liu, L Li, Q Li, N Tian, J Peng - Remote Sensing, 2022 - mdpi.com
Monitoring and early warning systems for landslides are urgently needed worldwide to
effectively reduce the losses of life and property caused by these natural disasters. Detecting …