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Prediction of soil corrosion rate of buried pipeline based on KPCA-GWO-SVM

In order to improve the prediction accuracy of soil corrosion rate of buried pipelines, the influencing factors of soil corrosion were sorted out and analyzed. The data dimensionality of influencing factors was reduced by Kernel Principal Component Analysis (KPCA), the key parameters of the Support...

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Wedi'i Gadw mewn:
Prif Awduron: Changjing LIANG, Bo XIE, Yanqing LIU, Zhijuan LIU, Ziqiang GUO, Chunyan REN, Qiongtao CHEN, Yichi LIU
Fformat: Artigo
Iaith:Chinês
Cyhoeddwyd: Editorial Office of Oil & Gas Storage and Transportation 2021-08-01
Cyfres:You-qi chuyun
Pynciau:
buried pipeline
soil corrosion
kernel principal component analysis (kpca)
grey wolf optimizer (gwo)
support vector machine (svm)
corrosion prediction
Mynediad Ar-lein:http://yqcy.xml-journal.net/cn/article/doi/10.6047/j.issn.1000-8241.2021.08.016
Tagiau: Ychwanegu Tag
Dim Tagiau, Byddwch y cyntaf i dagio'r cofnod hwn!

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