To read the full version of this content please select one of the options below:

Long-term prediction on atmospheric corrosion data series of carbon steel in China based on NGBM(1,1) model and genetic algorithm

Yuanjie Zhi (University of Science and Technology, Beijing, China)
Dongmei Fu (University of Science and Technology, Beijing, China)
Tao Yang (University of Science and Technology, Beijing, China)
Dawei Zhang (University of Science and Technology, Beijing, China)
Xiaogang Li (University of Science and Technology, Beijing, China)
Zibo Pei (University of Science and Technology, Beijing, China)

Anti-Corrosion Methods and Materials

ISSN: 0003-5599

Publication date: 1 July 2019

Abstract

Purpose

This study aims to achieve long-term prediction on a specific monotonic data series of atmospheric corrosion rate vs time.

Design/methodology/approach

This paper presents a new method, used to the collected corrosion data of carbon steel provided by the China Gateway to Corrosion and Protection, that combines non-linear gray Bernoulli model (NGBM(1,1) with genetic algorithm to attain the purpose of this study.

Findings

Results of the experiments showed that the present study’s method is more accurate than other algorithms. In particular, the mean absolute percentage error (MAPE) and the root mean square error (RMSE) of the proposed method in data sets are 9.15 per cent and 1.23 µm/a, respectively. Furthermore, this study illustrates that model parameter can be used to evaluate the similarity of curve tendency between two carbon steel data sets.

Originality/value

Corrosion data are part of a typical small-sample data set, and these also belong to a gray system because corrosion has a clear outcome and an uncertainly occurrence mechanism. In this work, a new gray forecast model was proposed to achieve the goal of long-term prediction of carbon steel in China.

Keywords

Acknowledgements

The authors would like to thank the National Natural Science Foundation of China (grant no. 51271032), the National Natural Science Foundation of China (grant no. 51131005) and the National Environmental Corrosion Platform for supporting this work.

Citation

Zhi, Y., Fu, D., Yang, T., Zhang, D., Li, X. and Pei, Z. (2019), "Long-term prediction on atmospheric corrosion data series of carbon steel in China based on NGBM(1,1) model and genetic algorithm", Anti-Corrosion Methods and Materials, Vol. 66 No. 4, pp. 403-411. https://doi.org/10.1108/ACMM-11-2017-1858

Publisher

:

Emerald Publishing Limited

Copyright © 2019, Emerald Publishing Limited