Addressing Data Imbalance in Hydrological Machine Learning: Impact of Advanced Sampling Methods on Performance and Interpretability

Na minha lista:

Detalhes bibliográficos
Publicado no:	Water Resources Research vol. 61, no. 10 (Oct 1, 2025)
Autor principal:	Yin, Xiaoran
Outros Autores:	Shu, Longcang, Wang, Zhe, Zhou, Long, Niu, Shuyao, Ren, Huazhun, Liu, Bo, Lu, Chengpeng
Publicado em:	John Wiley & Sons, Inc.
Assuntos:	Hydrologic data Datasets Algorithms Sampling methods Soil properties Hydraulic conductivity Hydrology Machine learning Hypercubes Random sampling Performance evaluation Learning algorithms Contamination Accuracy Soil sciences Training Groundwater Statistical sampling Decision making National forests Hydraulics Latin hypercube sampling Environmental
Acesso em linha:	Citation/Abstract Full Text Full Text - PDF
Tags:	Adicionar Tag Sem tags, seja o primeiro a adicionar uma tag!

Seja o primeiro a partilhar um comentário!