Illumination Uniformity Measurement Technology Research Based on Quasi-Sine Particle Swarm Optimization

Qing Hua Yao; Miao Cao

doi:10.4028/www.scientific.net/AMR.951.265

Paper Titles

Data Processing and Technology Application in Bayes and Empirical Bayes Reliability Analysis of Parameter of Ailamujia Distribution
p.249

Applied-Information Technology with Method of Digital Image Noise Processing
p.253

The Numerical Simulation of behind Armor Debris by Shaped Charge Jet Penetration
p.257

Research of USB OTG Technology in Image High-Speed Data Transfer
p.261

Illumination Uniformity Measurement Technology Research Based on Quasi-Sine Particle Swarm Optimization
p.265

An Integrated Architecture for Satellite Control Center System
p.269

Optimization Design of Structure and Parameters for RBF Neural Network Using Hybrid Hierarchy Genetic Algorithm
p.274

Information Technology in Human Physiological Signal Monitor System Based on Atmega328
p.278

Numerical Simulation of Dynamics in the Zero-Range Process Based on Applied Technology
p.282

HomeAdvanced Materials ResearchAdvanced Materials Research Vol. 951Illumination Uniformity Measurement Technology...

Illumination Uniformity Measurement Technology Research Based on Quasi-Sine Particle Swarm Optimization

Abstract:

Illumination uniformity measurement technology of target is a main factor that influences the instruments’ function assessing and ballistic test. Non-linear optimizing strategy of illumination uniformity is introduced in this paper, and the method is put forward to improve illumination uniformity based on Quasi-sine Particle Swarm Optimization. This paper describes the basic principle and implementation steps of the algorithm. The objective function and the degree of orientation function are given. The objective function of optimization results show that the algorithm is convergent and the overall lighting objectives of the symmetry are obtained.

You might also be interested in these eBooks

View Preview

Info:

Periodical:

Advanced Materials Research (Volume 951)

Pages:

265-268

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.951.265

Citation:

Cite this paper

Online since:

May 2014

Authors:

Qing Hua Yao*, Miao Cao

Keywords:

Illumination Measurement, Illumination Uniformity, Particle Swarm Optimization (PSO)

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

* - Corresponding Author

References

[1] GAO Ying, XIE Sheng-li, XU Ruo-ning, LI Zhao-hui. Blind Sparse Source Separation Based on Particle Swarm Optimization [J]. Journal of System Simulation, 2006, 18(8)：264-266.

Google Scholar

[2] CHEN De-bao, ZHAO Chun-xia. Ladder Particle Swarm Optimization and Application in Function Optimization, Journal of System Simulation, 2007. 12.

Google Scholar