Cargando…
Research on Micro/Nano Surface Flatness Evaluation Method Based on Improved Particle Swarm Optimization Algorithm
Flatness error is an important factor for effective evaluation of surface quality. The existing flatness error evaluation methods mainly evaluate the flatness error of a small number of data points on the micro scale surface measured by CMM, which cannot complete the flatness error evaluation of thr...
Autores principales: | Shu, Han, Zou, Chunlong, Chen, Jianyu, Wang, Shenghuai |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8714789/ https://www.ncbi.nlm.nih.gov/pubmed/34976973 http://dx.doi.org/10.3389/fbioe.2021.775455 |
Ejemplares similares
-
Image Classification and Recognition of Rice Diseases: A Hybrid DBN and Particle Swarm Optimization Algorithm
por: Lu, Yang, et al.
Publicado: (2022) -
A Tandem Robotic Arm Inverse Kinematic Solution Based on an Improved Particle Swarm Algorithm
por: Zhao, Guojun, et al.
Publicado: (2022) -
Orthogonal pinhole-imaging-based learning salp swarm algorithm with self-adaptive structure for global optimization
por: Wang, Zongshan, et al.
Publicado: (2022) -
Hybrid Swarming Algorithm With Van Der Waals Force
por: Yi, Zhang, et al.
Publicado: (2022) -
Application of an improved Discrete Salp Swarm Algorithm to the wireless rechargeable sensor network problem
por: Yi, Zhang, et al.
Publicado: (2022)