Cyanotoxin level prediction in a reservoir using gradient boosted regression trees: a case study
Sign Up to like & getrecommendations! Published in 2018 at "Environmental Science and Pollution Research"
DOI: 10.1007/s11356-018-2219-4
Abstract: Cyanotoxins are a type of cyanobacteria that is poisonous and poses a health threat in waters that could be used for drinking or recreational purposes. Thus, it is necessary to predict their presence to avoid… read more here.
Keywords: using gradient; gradient; boosted regression; prediction ... See more keywords
Modeling of photolytic degradation of sulfamethoxazole using boosted regression tree (BRT), artificial neural network (ANN) and response surface methodology (RSM); energy consumption and intermediates study.
Sign Up to like & getrecommendations! Published in 2021 at "Chemosphere"
DOI: 10.1016/j.chemosphere.2021.130151
Abstract: This study explores the boosted regression trees (BRT), artificial neural network (ANN) and response surface methodology (RSM) to model and optimize the operational variables for the simulation of the Photolytic degradation of Sulfamethoxazole (SMX) and… read more here.
Keywords: neural network; boosted regression; methodology; artificial neural ... See more keywords
Prediction Model of hospitalization time of COVID-19 patients based on Gradient Boosted Regression Trees
Sign Up to like & getrecommendations! Published in 2023 at "Mathematical Biosciences and Engineering"
DOI: 10.3934/mbe.2023459
Abstract: When an outbreak of COVID-19 occurs, it will cause a shortage of medical resources and the surge of demand for hospital beds. Predicting the length of stay (LOS) of COVID-19 patients is helpful to the… read more here.
Keywords: covid patients; gradient boosted; boosted regression; regression trees ... See more keywords