An enhanced extreme learning machine model for river flow forecasting: State-of-the-art, practical applications in water resource engineering area and future research …
Despite the massive diversity in the modeling requirements for practical hydrological
applications, there remains a need to develop more reliable and intelligent expert systems …
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 …
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
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 …
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 …
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 …
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
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 …
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 …
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 …
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; …
deformation during the rainy season are destructive for both residents and infrastructure; …
Remote sensing precursors analysis for giant landslides
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 …
effectively reduce the losses of life and property caused by these natural disasters. Detecting …