Mechanical Sciences
Mechanical Sciences
Mechanical Sciences
Articles | Volume 14, issue 2
Articles | Volume 14, issue 2
https://doi.org/10.5194/ms-14-361-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/ms-14-361-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 14, issue 2
Research article
 | 
06 Sep 2023
Research article |  | 06 Sep 2023

Multi-objective optimization design of parallel manipulators using a neural network and principal component analysis

Chao Yang, Peijiao Li, Yang Wang, Wei Ye, Tianze Sun, Fengli Huang, and Hui Zhang

Viewed

Total article views: 525 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
409 104 12 525 9 13
  • HTML: 409
  • PDF: 104
  • XML: 12
  • Total: 525
  • BibTeX: 9
  • EndNote: 13
Views and downloads (calculated since 06 Sep 2023)
Cumulative views and downloads (calculated since 06 Sep 2023)

Viewed (geographical distribution)

Total article views: 493 (including HTML, PDF, and XML) Thereof 493 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 02 Jul 2024
Download
Short summary
The main contribution of this work is to propose a multi-objective optimization design method in terms of factor analysis, a back-propagation (BP) neural network, principal component analysis (PCA), and a particle swarm optimization (PSO) algorithm to achieve optimal comprehensive performance of a mechanism. The computational cost of the proposed approach was reduced by 96.95 % compared with the PSO algorithm, and the comprehensive performance increased by 118.92 %.
Read more