Random forest regression for optimizing variable planting rates for corn and soybean using topographical and soil data
Sign Up to like & getrecommendations! Published in 2020 at "Agronomy Journal"
DOI: 10.1002/agj2.20442
Abstract: Correspondence MichaelA.Gore, PlantBreeding and Genetics Section, School of Integrative Plant Science,CornellUniversity, Ithaca, NY, 14853,USA Email:[email protected] Abstract In recent years, planting machinery that enables precise control of the planting rates has become available for corn (Zea… read more here.
Keywords: corn soybean; rate; soil; random forest ... See more keywords
Random forest regression to predict Farinograph traits from GlutoPeak output in wheat wild relative backcross lines
Sign Up to like & getrecommendations! Published in 2025 at "Cereal Chemistry"
DOI: 10.1002/cche.10860
Abstract: Flour quality is a key target of hard winter wheat breeding. The Farinograph is important for assessing quality before cultivar release in the United States, but large sample size requirements and long test times render… read more here.
Keywords: quality; forest regression; wheat; random forest ... See more keywords
Random forest regression for online capacity estimation of lithium-ion batteries
Sign Up to like & getrecommendations! Published in 2018 at "Applied Energy"
DOI: 10.1016/j.apenergy.2018.09.182
Abstract: Machine-learning based methods have been widely used for battery health state monitoring. However, the existing studies require sophisticated data processing for feature extraction, thereby complicating the implementation in battery management systems. This paper proposes a… read more here.
Keywords: capacity; battery; random forest; capacity estimation ... See more keywords
Simulation and analysis of evapotranspiration from desert grasslands based on a random forest regression model
Sign Up to like & getrecommendations! Published in 2025 at "Scientific Reports"
DOI: 10.1038/s41598-025-11056-0
Abstract: Evapotranspiration (ET) is a critical component of the water and energy cycles in desert grassland ecosystems. However, modeling ET in arid grasslands faces significant challenges due to data scarcity, high spatiotemporal heterogeneity, and complex interactions… read more here.
Keywords: regression model; forest regression; random forest; model ... See more keywords
The basicity analysis of sintered ore using laser-induced breakdown spectroscopy (LIBS) combined with random forest regression (RFR)
Sign Up to like & getrecommendations! Published in 2017 at "Analytical Methods"
DOI: 10.1039/c7ay01389b
Abstract: The basicity of sintered ore, which is related to the melting point of the sinter, is vital to ore mining and blast-furnace smelting. Laser-induced breakdown spectroscopy (LIBS) with random forest regression (RFR) has been applied… read more here.
Keywords: sintered ore; model; spectroscopy; random forest ... See more keywords
Random forest regression exploring contributing factors to artificial night-time lights observed in VIIRS satellite imagery
Sign Up to like & getrecommendations! Published in 2024 at "International Journal of Digital Earth"
DOI: 10.1080/17538947.2024.2324941
Abstract: ABSTRACT Artificial night-time lights (ANTL) pose environmental, economic, and social problems. To effectively manage this issue, it is important to understand the sources that contribute to it. Previous research has presented conflicting views on the… read more here.
Keywords: forest regression; random forest; viirs satellite; night time ... See more keywords
Enhanced Graphene-Based Metasurface Biosensor for Brain Tumor Detection and Behavior Prediction Using Random Forest Regression
Sign Up to like & getrecommendations! Published in 2025 at "Journal of The Electrochemical Society"
DOI: 10.1149/1945-7111/ade3a8
Abstract: This manuscript introduces a terahertz biosensor that integrates graphene-enhanced metasurfaces with a dual-resonator configuration for the accurate identification of brain cancers. The sensor comprises concentric circular resonators encircled by rectangular components on a silicon dioxide… read more here.
Keywords: detection; biosensor; brain; forest regression ... See more keywords
Microbiome Data Accurately Predicts the Postmortem Interval Using Random Forest Regression Models
Sign Up to like & getrecommendations! Published in 2018 at "Genes"
DOI: 10.3390/genes9020104
Abstract: Death investigations often include an effort to establish the postmortem interval (PMI) in cases in which the time of death is uncertain. The postmortem interval can lead to the identification of the deceased and the… read more here.
Keywords: postmortem interval; regression models; postmortem; random forest ... See more keywords
Prediction of aqueous intrinsic solubility of druglike molecules using Random Forest regression trained with Wiki-pS0 database
Sign Up to like & getrecommendations! Published in 2020 at "ADMET and DMPK"
DOI: 10.5599/admet.766
Abstract: The accurate prediction of solubility of drugs is still problematic. It was thought for a long time that shortfalls had been due the lack of high-quality solubility data from the chemical space of drugs. This… read more here.
Keywords: intrinsic solubility; database; solubility; random forest ... See more keywords