Enhancing Groundwater Recharge Prediction: A Feature Selection‐Based Deep Forest Model With Bayesian Optimisation
Bao Liu,
Yaohua Sun,
Lei Gao
Abstract:Accurate prediction of groundwater recharge is crucial for the sustainable management of water resources. Existing models, while effective, still have potential for improved accuracy. This study proposed a novel deep forest model—the Feature Selection‐based Deep Forest model (FSDF)—for enhanced groundwater recharge prediction. This model consists of three key essential components: a feature selection layer, a cascade enhancement layer and a decision output layer, all designed to enhance the prediction accuracy… Show more
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.