An interpretable IGWO-MKRVM model for predicting excavation damaged zone thickness of drift
R
Ruzi Yang
G
Guangquan Zhang
Y
Yicheng Ye
(National Medical Products Administration Key Laboratory for Research and Evaluation of Drug Metabolism and Guangdong Provincial Key Laboratory of New Drug Screening, School of Pharmaceutical Sciences, Southern Medical University)
M
Mingchao Wan
Article Details
Journal
Scientific Reports
Volume / Issue
Vol. 16, Issue 1
Published
March 14, 2026
ISSN
2045-2322
Publisher
Nature Portfolio
Authors (4)
R
Ruzi Yang
G
Guangquan Zhang
Y
Yicheng Ye
National Medical Products Administration Key Laboratory for Research and Evaluation of Drug Metabolism and Guangdong Provincial Key Laboratory of New Drug Screening, School of Pharmaceutical Sciences, Southern Medical University
M
Mingchao Wan
Related Articles from this Journal
AI models of unstable flow exhibit hallucination
Ramdhan Wibawa, Birendra Jha
Aug 2026
10.1038/s41598-026-64023-8
The MCAA-YOLO + XPBI integrated model provides a hybrid intelligent measurement method for predicting the body weight of Hu sheep
Hang Zhang, Yuang Cheng et al.
Aug 2026
10.1038/s41598-026-64075-w
Application of iron nano-biofertilizers as a sustainable approach to enhance growth and micronutrient uptake in soybean
Ava Mohrazi, Reza Ghasemi-Fasaei
Aug 2026
10.1038/s41598-026-66011-4
Adolescents’ status-dependent public and private conformity to prosocial and antisocial decisions in a public goods game
Niloofar Saeedi, Khatereh Borhani et al.
Aug 2026
10.1038/s41598-026-64831-y
An explainable hierarchical capsule network framework for supporting expert sensory evaluation of herbal medicines with natural language generation
Hyein Lee, Dae-Hyun Jung
Aug 2026
10.1038/s41598-026-64156-w