Machine learning brings new insights for reducing salinization disaster

Machine learning brings new insights for reducing salinization disaster

This study constructs a machine learning system to examine the predictors of soil salinity in deserts. We conclude that soil humidity and subterranean CO2 concentration are two leading controls of soil salinity—respectively explain 71.33%, 13.83% in the data. The (R2, root-mean-square error, RPD) va...

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Bibliographic Details
Main Authors: Peng An, Wenfeng Wang, Xi Chen, Zhikai Zhuang, Lujie Cui
Format: Article
Language:English
Published: Frontiers Media S.A. 2023-02-01
Series:Frontiers in Earth Science
Subjects:
salinization disaster
principal components analysis (PCA)
artificial neural network (ANN)
long short-term memory (LSTM)
subterranean CO2 sequestration
Online Access:https://www.frontiersin.org/articles/10.3389/feart.2023.1130070/full

Internet

https://www.frontiersin.org/articles/10.3389/feart.2023.1130070/full

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