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- W2898282009 abstract "Summary In view of the fact that the corrosiveness of seamless steel tubes under actual conditions was difficult to predict, the main influencing factors of seamless oil tube corrosion under actual conditions were analyzed, and a model for predicting the corrosion of seamless oil tubes was constructed. The algorithm of the extension neural network was introduced. The Python language was used to implement the extensible neural network algorithm, and the influencing factors of steel tube corrosion were trained. The extension neural network was simulated and verified, and finally, the system is implemented by the mobile APP." @default.
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- W2898282009 date "2018-10-24" @default.
- W2898282009 modified "2023-10-16" @default.
- W2898282009 title "An improved prediction algorithm of seamless tubing corrosion based on an extension neural network" @default.
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- W2898282009 doi "https://doi.org/10.1002/cpe.4801" @default.
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