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

Bewaard in:

Bibliografische gegevens
Gepubliceerd in:	Water Resources Research vol. 61, no. 10 (Oct 1, 2025)
Hoofdauteur:	Yin, Xiaoran
Andere auteurs:	Shu, Longcang, Wang, Zhe, Zhou, Long, Niu, Shuyao, Ren, Huazhun, Liu, Bo, Lu, Chengpeng
Gepubliceerd in:	John Wiley & Sons, Inc.
Onderwerpen:	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
Online toegang:	Citation/Abstract Full Text Full Text - PDF
Tags:	Voeg label toe Geen labels, Wees de eerste die dit record labelt!

Wees de eerste die reageert!