Evolutionary support vector regression algorithm applied to the prediction of the thickness of the chromium layer in a hard chromium plating process

作者：

Highlights：

• An evolutionary SVR model is proposed to evaluate the thickness of the chromium layer in a hard chromium plating process.

• Comparison between the evolutionary SVR and ANN-DOE models is carried out.

• The evolutionary SVR technique can deal with success this highly nonlinear industrial problem.

摘要

•An evolutionary SVR model is proposed to evaluate the thickness of the chromium layer in a hard chromium plating process.•Comparison between the evolutionary SVR and ANN-DOE models is carried out.•The evolutionary SVR technique can deal with success this highly nonlinear industrial problem.

论文关键词：Hard chromium plating process,Support vector machines for regression (SVR),Machine learning,Evolutionary algorithms (EAs),Evolutionary support vector machines (ESVMs)

论文评审过程：Available online 2 December 2013.

论文官网地址：https://doi.org/10.1016/j.amc.2013.11.031