Quantum simulation for high-energy physics
It is for the first time that quantum simulation for high-energy physics (HEP) is studied in the
US decadal particle-physics community planning, and in fact until recently, this was not …
US decadal particle-physics community planning, and in fact until recently, this was not …
Machine learning methods for landslide susceptibility studies: A comparative overview of algorithm performance
Landslides are one of the catastrophic natural hazards that occur in mountainous areas,
leading to loss of life, damage to properties, and economic disruption. Landslide …
leading to loss of life, damage to properties, and economic disruption. Landslide …
Improved landslide assessment using support vector machine with bagging, boosting, and stacking ensemble machine learning framework in a mountainous …
Heavy rainfall in mountainous terrain can trigger numerous landslides in hill slopes. These
landslides can be deadly to the community living downslope with their fast pace, turning …
landslides can be deadly to the community living downslope with their fast pace, turning …
Convolutional neural network (CNN) with metaheuristic optimization algorithms for landslide susceptibility mapping in Icheon, South Korea
Landslides are a geological hazard that can pose a serious threat to human health and the
environment of highlands or mountain slopes. Landslide susceptibility mapping is an …
environment of highlands or mountain slopes. Landslide susceptibility mapping is an …
[HTML][HTML] 基于优化负样本采样策略的梯度提升决策树与随机森林的汶川同震滑坡易发性评价
郭衍昊， 窦杰， 向子林， 马豪， 董傲男， 罗万祺 - 地质科技通报, 2024 - dzkjqb.cug.edu.cn
强震诱发的滑坡具有数量多, 分布广, 规模大等特点, 严重威胁人民生命财产安全.
滑坡易发性评价能够快速预测灾害空间分布, 对于减轻震后灾害的危险性具有重要意义 …
滑坡易发性评价能够快速预测灾害空间分布, 对于减轻震后灾害的危险性具有重要意义 …
[HTML][HTML] Geomorphometry and terrain analysis: Data, methods, platforms and applications
Terrain is considered one of the most essential natural geographic features and is a key
factor in physical processes. Geomorphometry and terrain analyses have provided a wealth …
factor in physical processes. Geomorphometry and terrain analyses have provided a wealth …
A spatially explicit deep learning neural network model for the prediction of landslide susceptibility
With the increasing threat of recurring landslides, susceptibility maps are expected to play a
bigger role in promoting our understanding of future landslides and their magnitude. This …
bigger role in promoting our understanding of future landslides and their magnitude. This …
[HTML][HTML] DEM resolution effects on machine learning performance for flood probability mapping
Floods are among the devastating natural disasters that occurred very frequently in arid
regions during the last decades. Accurate assessment of the flood susceptibility mapping is …
regions during the last decades. Accurate assessment of the flood susceptibility mapping is …
Different sampling strategies for predicting landslide susceptibilities are deemed less consequential with deep learning
Predictive capability of landslide susceptibilities is assumed to be varied with different
sampling techniques, such as (a) the landslide scarp centroid,(b) centroid of landslide …
sampling techniques, such as (a) the landslide scarp centroid,(b) centroid of landslide …
Analysis of land use and land cover using machine learning algorithms on google earth engine for Munneru River Basin, India
KN Loukika, VR Keesara, V Sridhar - Sustainability, 2021 - mdpi.com
The growing human population accelerates alterations in land use and land cover (LULC)
over time, putting tremendous strain on natural resources. Monitoring and assessing LULC …
over time, putting tremendous strain on natural resources. Monitoring and assessing LULC …