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| Application of GA-BP Artificial Neural Network in Seawater Corrosion Prediction of Copper Alloys |
| Received:April 18, 2021 Revised:June 16, 2021 |
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| DOI：10.7643/issn.1672-9242.2021.12.012 |
| KeyWord:GA-BP artificial neural network copper seawater corrosion |
| Author | Institution |
| ZHANG Peng-hui |
State Key Laboratory for Marine Corrosion and Protection, Luoyang Ship Material Research Institute, Qingdao , China |
| XIAO You-an |
Wuhan University of Technology, Wuhan , China |
| ZHAO Jian-cang |
State Key Laboratory for Marine Corrosion and Protection, Luoyang Ship Material Research Institute, Qingdao , China |
| DING Kang-kang |
State Key Laboratory for Marine Corrosion and Protection, Luoyang Ship Material Research Institute, Qingdao , China |
| HOU Jian |
State Key Laboratory for Marine Corrosion and Protection, Luoyang Ship Material Research Institute, Qingdao , China |
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| Abstract: |
| This paper aims to take full advantage of corrosion data and deeply analyze corrosion law. The genetic algorithm (GA) was introduced to improve the back propagation (BP) artificial neural network (ANN), with a view to overcome the inherent defect of ANN and increase prediction accuracy and training speed. In this paper, a brief interpretation of GA-BP artificial neural network was given. And based on the corrosion data of copper in marine environment, the GA-BP artificial neural network method was applied to the building process of marine corrosion prediction model. The experimental results showed that the model can meet the design requirements and had good generalization ability. |
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