Data - Driven Prediction of Corrosion Rate of 3C Steel in Marine Environment

ZHAI Xiuyun, CHEN Mingtong

doi:10.16577/j.issn.1001-1560.2022.0275

Materials Protection >

2022 , Vol. 55 >Issue 10: 50 - 55

DOI: https://doi.org/10.16577/j.issn.1001-1560.2022.0275

Data - Driven Prediction of Corrosion Rate of 3C Steel in Marine Environment

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(Public Experiment Center,Panzhihua University,Panzhihua 617000,China)

Received date: 2022-03-25

Revised date: 2022-05-09

Accepted date: 2022-06-14

Online published: 2023-12-23

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Abstract

For predicting the corrosion rate of 3C steel quickly and accurately,a support vector regression (RBF-SVR) model based on Gaussian kernel function and an ensemble model based on three models were developed using the data obtained from literatures.The RBF-SVR model was established after dimension reduction of the data set realized respectively through the SVR-based genetic algorithm,forward algorithm and backward algorithm,and after optimizing super-parameter using leave-one-out cross validation method and grid search.Finally,the obtained model and two other models from published literatures (GA-BPNN model and BPNN model with four layers) were integrated to form an ensemble model.The research results indicated that the ensemble model had higher prediction accuracy and generalization ability.

Key words： 3C steel; corrosion rate; support vector regression; prediction model; marine environment

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ZHAI Xiuyun, CHEN Mingtong . Data - Driven Prediction of Corrosion Rate of 3C Steel in Marine Environment[J]. Materials Protection, 2022 , 55(10) : 50 -55 . DOI: 10.16577/j.issn.1001-1560.2022.0275

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