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Monitoring Forest Carbon Sequestration with Remote Sensing

2023

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Revealing the sources of arsenic in private well water using Random Forest Classification and Regression

The Science of the total environment, 2023-01, Vol.857, p.159360-159360, Article 159360

2023

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Assessment of landslide susceptibility mapping based on Bayesian hyperparameter optimization: A comparison between logistic regression and random forest

Engineering geology, 2021-02, Vol.281, p.105972, Article 105972

2021

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Land Cover Classification using Google Earth Engine and Random Forest Classifier—The Role of Image Composition

Remote sensing (Basel, Switzerland), 2020-08, Vol.12 (15), p.2411

2020

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A comparative study of logistic model tree, random forest, and classification and regression tree models for spatial prediction of landslide susceptibility

Catena (Giessen), 2017-04, Vol.151, p.147-160

2017

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Improved random forest algorithms for increasing the accuracy of forest aboveground biomass estimation using Sentinel-2 imagery

Ecological indicators, 2024-02, Vol.159, p.111752, Article 111752

2024

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Oblique and rotation double random forest

Neural networks, 2022-09, Vol.153, p.496-517

2022

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A hybrid optimization method of factor screening predicated on GeoDetector and Random Forest for Landslide Susceptibility Mapping

Geomorphology (Amsterdam, Netherlands), 2021-04, Vol.379, p.107623, Article 107623

2021

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A spatial downscaling approach for the SMAP passive surface soil moisture product using random forest regression

Journal of hydrology (Amsterdam), 2018-08, Vol.563, p.1009-1024

2018

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Advances in global bioavailable strontium isoscapes

Palaeogeography, palaeoclimatology, palaeoecology, 2020-10, Vol.555, p.109849, Article 109849

2020

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Hypothesis margin based ensemble method for the classification of noisy remote sensing data

IEEE transactions on geoscience and remote sensing, 2023-01, Vol.61, p.1-1

2023

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Soil moisture forecasting by a hybrid machine learning technique: ELM integrated with ensemble empirical mode decomposition

Geoderma, 2018-11, Vol.330, p.136-161

2018

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Multiscale groundwater level forecasting: Coupling new machine learning approaches with wavelet transforms

Advances in water resources, 2020-07, Vol.141, p.103595, Article 103595

2020

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Comparison of random forests and support vector machine for real-time radar-derived rainfall forecasting

Journal of hydrology (Amsterdam), 2017-09, Vol.552, p.92-104

2017

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Sampling design optimization for soil mapping with random forest

Geoderma, 2019-12, Vol.355, p.113913, Article 113913

2019

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From Easy to Hopeless-Predicting the Difficulty of Phylogenetic Analyses

Molecular biology and evolution, 2022-12, Vol.39 (12)

2022

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Hyperspectral inversion of soil heavy metals in Three-River Source Region based on random forest model

Catena (Giessen), 2021-07, Vol.202, p.105222, Article 105222

2021

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Multiple Instance Learning With Random Forest for Event Logs Analysis and Predictive Maintenance in Ship Electric Propulsion System

IEEE transactions on industrial informatics, 2022-11, Vol.18 (11), p.7718-7728

2022

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Landslide susceptibility mapping using random forest, boosted regression tree, classification and regression tree, and general linear models and comparison of their performance at Wadi Tayyah Basin, Asir Region, Saudi Arabia

Landslides, 2016-10, Vol.13 (5), p.839-856

2016

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Modular Multi-Tree Genetic Programming for Evolutionary Feature Construction for Regression

IEEE transactions on evolutionary computation, 2024, p.1-1

2024

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An ensemble of decision trees with random vector functional link networks for multi-class classification

Applied soft computing, 2018-09, Vol.70, p.1146-1153

2018

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A synthesis framework using machine learning and spatial bivariate analysis to identify drivers and hotspots of heavy metal pollution of agricultural soils

Environmental pollution (1987), 2021-10, Vol.287, p.117611-117611, Article 117611

2021

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Tuning spatial parameters of Geographical Random Forest: the case of agricultural drought

Acta Universitatis Carolinae. Geographica, 2023-11, Vol.58 (2), p.187-199

Bicák, Daniel

2023

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Investigation of the spatial and temporal variation of soil salinity using random forests in the central desert of Iran

Geoderma, 2020-04, Vol.365, p.114233, Article 114233

2020

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Rapidly assessing earthquake-induced landslide susceptibility on a global scale using random forest

Geomorphology (Amsterdam, Netherlands), 2021-10, Vol.391, p.107889, Article 107889

2021

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