Prediction of ground-level ozone by SOM-NARX hybrid neural network based on the correlation of predictors.
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ABSTRACT:
SUBMITTER: Xiong Q
PROVIDER: S-EPMC9732375 | biostudies-literature | 2022 Dec
REPOSITORIES: biostudies-literature
Publications
Prediction of ground-level ozone by SOM-NARX hybrid neural network based on the correlation of predictors.
Xiong Qinqing Q Wang Wenju W Wang Mingya M Zhang Chunhui C Zhang Xuechun X Chen Chun C Wang Mingshi M
iScience 20221123 12
Current approaches to ozone prediction using hybrid neural networks are numerous but not perfect. Decomposition algorithms ignore the correlation between predictors and ozone, and feature extraction methods rarely select appropriate predictors in terms of correlation, especially for VOCs. Therefore, this study proposes a hybrid neural network model SOM-NARX based on the correlation of predictors. The model is based on MIC to filter predictors, using SOM to make predictors as feature sequences an ...[more]
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