[HTML][HTML] A review of ensemble learning and data augmentation models for class imbalanced problems: combination, implementation and evaluation
Class imbalance (CI) in classification problems arises when the number of observations
belonging to one class is lower than the other. Ensemble learning combines multiple models …
belonging to one class is lower than the other. Ensemble learning combines multiple models …
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 …
Brain-computer interface: Advancement and challenges
Brain-Computer Interface (BCI) is an advanced and multidisciplinary active research domain
based on neuroscience, signal processing, biomedical sensors, hardware, etc. Since the …
based on neuroscience, signal processing, biomedical sensors, hardware, etc. Since the …
[HTML][HTML] A hybrid ensemble-based deep-learning framework for landslide susceptibility mapping
Landslides are highly hazardous geological disasters that can potentially threaten the safety
of human life and property. As a result, landslide susceptibility mapping (LSM) plays an …
of human life and property. As a result, landslide susceptibility mapping (LSM) plays an …
[HTML][HTML] Landslide susceptibility zonation method based on C5. 0 decision tree and K-means cluster algorithms to improve the efficiency of risk management
Abstract Machine learning algorithms are an important measure with which to perform
landslide susceptibility assessments, but most studies use GIS-based classification methods …
landslide susceptibility assessments, but most studies use GIS-based classification methods …
[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 …
Prediction of compressive strength of fly ash based concrete using individual and ensemble algorithm
Machine learning techniques are widely used algorithms for predicting the mechanical
properties of concrete. This study is based on the comparison of algorithms between …
properties of concrete. This study is based on the comparison of algorithms between …
[HTML][HTML] Ensemble learning framework for landslide susceptibility mapping: Different basic classifier and ensemble strategy
The application of ensemble learning models has been continuously improved in recent
landslide susceptibility research, but most studies have no unified ensemble framework …
landslide susceptibility research, but most studies have no unified ensemble framework …
A comparative study of heterogeneous ensemble-learning techniques for landslide susceptibility mapping
This study introduces four heterogeneous ensemble-learning techniques, that is, stacking,
blending, simple averaging, and weighted averaging, to predict landslide susceptibility in …
blending, simple averaging, and weighted averaging, to predict landslide susceptibility in …
Landslide detection from an open satellite imagery and digital elevation model dataset using attention boosted convolutional neural networks
Convolution neural network (CNN) is an effective and popular deep learning method which
automatically learns complicated non-linear mapping from original inputs to given labels or …
automatically learns complicated non-linear mapping from original inputs to given labels or …