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- W2029168295 abstract "By analyzing the climatic factors and aluminum alloys corrosion data in 10 atmospheric corrosion sites, the aluminum alloy atmospheric corrosion prediction model was built. The reasonableness of the corrosion model was verified by using the BP artificial neural network to learn, train, simulate, and compare with the corrosion test results of aluminum alloy samples in 10 typical atmospheric corrosion test stations. The results show that a stable forecasting model can be built based on the BP artificial neural network, which well predicted the corrosion rates of aluminum alloys in 10 typical atmospheric corrosion test stations." @default.
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- W2029168295 date "2013-01-01" @default.
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- W2029168295 title "Research on Corrosion Rate Prediction of Aluminum Alloys in Typical Domestic Areas Based on BP Artificial Neural Network" @default.
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- W2029168295 doi "https://doi.org/10.4028/www.scientific.net/amr.652-654.1088" @default.
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