Prediction Model of Corrosion Current Density Induced by Stray Current Based on QPSO-Driven Neural Network
Joint Authors
Li, Wei
Xin, Gaifang
Wang, Chengtao
Wang, Yuqiao
Xu, Shaoyi
Source
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-15, 15 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-10-31
Country of Publication
Egypt
No. of Pages
15
Main Subjects
Abstract EN
The buried pipelines and metallic structures in subway systems are subjected to electrochemical corrosion under the stray current interference.
The corrosion current density determines the degree and the speed of stray current corrosion.
A method combining electrochemical experiment with the machine learning algorithm was utilized in this research to study the corrosion current density under the coupling action of stray current and chloride ion.
In this study, a quantum particle swarm optimization-neural network (QPSO-NN) model was built up to predict the corrosion current density in the process of stray current corrosion.
The QPSO algorithm was employed to optimize the updating process of weights and biases in the artificial neural network (ANN).
The results show that the accuracy of the proposed QPSO-NN model is better than the model based on backpropagation neural network (BPNN) and particle swarm optimization-neural network (PSO-NN).
The accuracy distribution of the QPSO-NN model is more stable than that of the BPNN model and the PSO-NN model.
The presented model can be used for the prediction of corrosion current density and provides the possibility to monitor the stray current corrosion in subway system through an intelligent learning algorithm.
American Psychological Association (APA)
Wang, Chengtao& Li, Wei& Xin, Gaifang& Wang, Yuqiao& Xu, Shaoyi. 2019. Prediction Model of Corrosion Current Density Induced by Stray Current Based on QPSO-Driven Neural Network. Complexity،Vol. 2019, no. 2019, pp.1-15.
https://search.emarefa.net/detail/BIM-1131414
Modern Language Association (MLA)
Wang, Chengtao…[et al.]. Prediction Model of Corrosion Current Density Induced by Stray Current Based on QPSO-Driven Neural Network. Complexity No. 2019 (2019), pp.1-15.
https://search.emarefa.net/detail/BIM-1131414
American Medical Association (AMA)
Wang, Chengtao& Li, Wei& Xin, Gaifang& Wang, Yuqiao& Xu, Shaoyi. Prediction Model of Corrosion Current Density Induced by Stray Current Based on QPSO-Driven Neural Network. Complexity. 2019. Vol. 2019, no. 2019, pp.1-15.
https://search.emarefa.net/detail/BIM-1131414
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1131414