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- W2352102252 abstract "The neural network model is applied to predict the corrosion rate in the refinery.The field data is sorted out and analyzed.The neural network model is trained and the mathematical model for corrosion rate prediction is established.The improved Levenberg-Marquardt algorithm is used to train the model and this algorithm is better than the traditional gradient-descent algorithm for the algorithm convergence.Corrosion data can be included in the existing corrosion models by neural network modeling to facilitate data management and inquiry;meanwhile,the model can predict the relationship between the on-site parameters and corrosion rate.The average variance between the predicted value and the actual value is 0.013 2 which can meet the field needs." @default.
- W2352102252 created "2016-06-24" @default.
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- W2352102252 date "2013-01-01" @default.
- W2352102252 modified "2023-09-23" @default.
- W2352102252 title "APPLICATION OF CORROSION RATE PREDICTION MODEL BASED ON BP NEURAL NETWORK IN REFINERY" @default.
- W2352102252 hasPublicationYear "2013" @default.
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