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Spatial Mapping of the Groundwater Potential of the Geum River Basin Using Ensemble Models Based on Remote Sensing Images

Remote Sensing, 2019
This study analyzed the Groundwater Productivity Potential (GPP) of Okcheon city, Korea, using three different models. Two of these three models are data mining models: Boosted Regression Tree (BRT) model and Random Forest (RF) model.
Jeong-Cheol Kim, Hyung-Sup Jung, Saro Lee +2 more
doaj +1 more source

Predicting the Young’s Modulus of Rock Material Based on Petrographic and Rock Index Tests Using Boosting and Bagging Intelligence Techniques

Applied Sciences, 2022
Rock deformation is considered one of the essential rock properties used in designing and constructing rock-based structures, such as tunnels and slopes.
Long Tsang +4 more
doaj +1 more source

Investigating the effect of sound in horror clip on the cardiac electrophysiology of young adults using wavelet packet decomposition and machine learning classifiers

Biomedical Engineering Advances, 2022
The effect of horror sound on electro-cardiac activity is not yet sufficiently explored despite recommendable research on different genres of music and sound. Detecting the impact of these stimuli is a complex task.
Bikash K. Pradhan +6 more
doaj +1 more source

Link Adaptation on an Underwater Communications Network Using Machine Learning Algorithms: Boosted Regression Tree Approach

IEEE Access, 2020
Interest in the study of next-generation underwater sensor networks for ocean investigations has increased owing to developing concerns over their utilization in areas such as oceanography, commercial operations in maritime areas, and military ...
M.S.M. Alamgir, Mst. Najnin Sultana, Kyunghi Chang +2 more
doaj +1 more source

The fitting interactions of the association among humidity, windspeed, SO₂ and HFRS cases in Shenyang, 2014–2019 based on the boosted regression tree models.

, 2023
The fitting interactions of the association among humidity, windspeed, SO2 and HFRS cases in Shenyang, 2014–2019 based on the boosted regression tree models.
Ye Chen (241426) +2 more
core +1 more source

Appendix F. Variable importance for generalized linear models (GLM), generalized additive models (GAM), and boosted regression tree models (BRT) based on species cover data.

, 2016
Variable importance for generalized linear models (GLM), generalized additive models (GAM), and boosted regression tree models (BRT) based on species cover ...
Peter C. le Roux (2925273) +4 more
core +2 more sources

Ensemble ecological niche modeling of West Nile virus probability in Florida.

PLoS ONE, 2021
Ecological Niche Modeling is a process by which spatiotemporal, climatic, and environmental data are analyzed to predict the distribution of an organism. Using this process, an ensemble ecological niche model for West Nile virus habitat prediction in the
Sean P Beeman +3 more
doaj +1 more source

Summary of Boosted Regression Tree Models.

, 2013
Summary of Boosted Regression Tree Models.
Israel Del Toro (433266)
core +1 more source

Machine Learning Approaches for Soil Moisture Prediction Using Ground Penetrating Radar: A Comparative Study of Tree-Based Algorithms

Earth
Accurate soil moisture estimation is critical for precision agriculture and water resource management, yet traditional sampling methods are time-consuming, destructive, and provide limited spatial coverage.
Jantana Panyavaraporn +3 more
doaj +1 more source

Comparison of multi-criteria-analytical hierarchy process and machine learning-boosted tree models for regional flood susceptibility mapping: a case study from Slovakia

Geomatics, Natural Hazards & Risk, 2021
Identification of areas susceptible to floods is an important issue which requires an increased attention due to the changing frequency and magnitude of floods, which is mainly a result of the ongoing climate change and increasing anthropic pressure on ...
Matej Vojtek +8 more
doaj +1 more source

machine learning
random forest
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