Optimization of gear blank preforms based on a new R-GPLVM model utilizing GA-ELM

作者：

Highlights：

• A novel R-GPLVM is proposed to screen out critical dimensions of the preform.

• A newly GA-ELM framework seamlessly integrated with R-GPLVM is proposed.

• Discussions demonstrate that Gaussian kernel function has the higher accuracy.

• The relevant parameters of ELM are optimized with the improved performance.

• Engineering applications and FEM validate the feasibility of the proposed method.

摘要

•A novel R-GPLVM is proposed to screen out critical dimensions of the preform.•A newly GA-ELM framework seamlessly integrated with R-GPLVM is proposed.•Discussions demonstrate that Gaussian kernel function has the higher accuracy.•The relevant parameters of ELM are optimized with the improved performance.•Engineering applications and FEM validate the feasibility of the proposed method.

论文关键词：Preform optimization,R-GPLVM,ELM,Gear blank,GA

论文评审过程：Received 15 April 2014, Revised 9 March 2015, Accepted 13 March 2015, Available online 24 March 2015.

论文官网地址：https://doi.org/10.1016/j.knosys.2015.03.010