Prediction Model for Corrosion of Aluminum Alloys Based on Artificial Neural network and Analysis of the Precision

J Chin Soc Corr Pro

2004, Vol. 24

Issue (4): 218-221 DOI:

Research Report

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Prediction Model for Corrosion of Aluminum Alloys Based on Artificial Neural network and Analysis of the Precision

Xiaoming Tan

海军航空工程学院学员旅

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Abstract A prediction model for corrosion damage of aluminum alloys was developed and the nonlinear relationship between maximum corrosion depth, fatigue performance and corrosion temperature, corrosion time was established based on MATLAB, using BP(Back Propagation) algorithm of neural network. The corrosion trend of aluminum alloys can be predicted by this means. Four-layer network and three-layer network were used, and the effects of structure model of neural network on the precision were discussed. The results show that the former is more precise than the latter.

Key words: neural network fatigue corrosion prediction aluminum alloys

Received: 30 June 2003

ZTFLH:

TG172

Corresponding Authors: Xiaoming Tan

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Xiaoming Tan. Prediction Model for Corrosion of Aluminum Alloys Based on Artificial Neural network and Analysis of the Precision. J Chin Soc Corr Pro, 2004, 24(4): 218-221 .

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https://www.jcscp.org/EN/ OR https://www.jcscp.org/EN/Y2004/V24/I4/218

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