Quality Control Method Based on Quantum Genetic Clustering Algorithm

Authors

Wang Jie, School of Internet of Things Engineering, Jiangnan University, Wuxi 214122, China;
Wang Yan, School of Internet of Things Engineering, Jiangnan University, Wuxi 214122, China;

Abstract

Abstract: This paper proposes a method of quality control chart recognition based on Quantum Genetic Clustering Algorithm. This method is divided into two parts: quality feature extraction and pattern classification. By combining Quantum Genetic Algorithm(QGA) and K-means algorithm, a quantum genetic clustering algorithm based on a mechanism for determining the rotation direction of a quantum rotary gate is proposed, and its performance is verified by experimental simulation. Based on the clustering analysis of quality data using the quantum genetic algorithm proposed in this paper, a control chart feature description method is proposed. With this feature as input, Support Vector Machine is used to identify the corresponding quality control chart pattern.The proposed quantum genetic clustering algorithm obtains better clustering results,and the accuracy of the proposed control chart recognition method reaches 98.63%.

Recommended Citation

Jie, Wang and Yan, Wang (2019) "Quality Control Method Based on Quantum Genetic Clustering Algorithm," Journal of System Simulation: Vol. 31: Iss. 12, Article 4.
DOI: 10.16182/j.issn1004731x.joss.19-FZ0256
Available at: https://dc-china-simulation.researchcommons.org/journal/vol31/iss12/4

First Page

2591

Revised Date

2019-06-26

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.19-FZ0256

Last Page

2599

CLC

TP391.9

Recommended Citation

Wang Jie, Wang Yan. Quality Control Method Based on Quantum Genetic Clustering Algorithm[J]. Journal of System Simulation, 2019, 31(12): 2591-2599.

DOI

10.16182/j.issn1004731x.joss.19-FZ0256