Work

Optimizing methane flux prediction and key feature identification based on a novel hybrid machine learning model

Year: 2025

Type: article

Abstract: prediction of different site types.

Source: iScience

DOI: 10.1016/j.isci.2025.114011

Authors: Xinqin Gu, Li Yao, Xiang Xiao, Lifeng Wu, Haofeng Yu

Institutions: Jiangxi University of Water Resources and Electric Power, Kunming University of Science and Technology, China Institute of Water Resources and Hydropower Research, State Key Laboratory of Basin Water Cycle Simulation and Regulation

Language: English

Topic: Atmospheric and Environmental Gas Dynamics

Subfield: Global and Planetary Change

Field: Environmental Science

Domain: Physical Sciences

SDG: Climate action

Open Access status: gold

Estimated APC paid: $3,240

Funder: National Natural Science Foundation of China

Award: G1476582674

OpenAlex ID: W4416185376

FWCI: 1.713

Cites: 39

Cited by: 4

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