A machine learning and genetic algorithm-based method for predicting width deviation of hot-rolled strip in steel production systems

Yingjun Ji, Shixin Liu, Mengchu Zhou, Ziyan Zhao, Xiwang Guo, Liang Qi

Research output: Contribution to journalArticlepeer-review

Abstract

Width deviation is an important metric for evaluating the quality of a hot-rolled strip in steel production systems. This paper considers a width deviation prediction problem and proposes a Machine-learning and Genetic-algorithm-based Hybrid method named MGH to obtain a prediction model. Existing work mainly focuses on high prediction accuracy, while ignoring interpretability. This work aims to build a prediction model that can make a good trade-off between two industry-required criteria, i.e., prediction accuracy and interpretability. It first collects some process variables in a hot rolling process and includes them as well as some constructed variables in a feature pool. Then we propose MGH to find representative variables from it and build a prediction model. MGH results from the integration of hierarchical clustering, genetic algorithm, and generalized linear regression. In detail, hierarchical clustering is applied to divide variables into clusters. Genetic algorithm and generalized linear regression are innovatively combined to select a representative variable from each cluster and develop a prediction model. The computational experiments conducted on both industrial and public datasets show that the proposed method can effectively balance prediction accuracy and interpretability of its resulting model. It has better overall performance than the compared state-of-the-art models.

Original languageEnglish (US)
Pages (from-to)360-375
Number of pages16
JournalInformation sciences
Volume589
DOIs
StatePublished - Apr 2022

All Science Journal Classification (ASJC) codes

  • Software
  • Control and Systems Engineering
  • Theoretical Computer Science
  • Computer Science Applications
  • Information Systems and Management
  • Artificial Intelligence

Keywords

  • Feature construction
  • Generalized linear regression
  • Genetic algorithm
  • Hierarchical clustering
  • Hot-rolled strip
  • Width deviation prediction

Fingerprint

Dive into the research topics of 'A machine learning and genetic algorithm-based method for predicting width deviation of hot-rolled strip in steel production systems'. Together they form a unique fingerprint.

Cite this