Feature Selection Optimization for Mahalanobis-Taguchi System with Binary Quantum Behavior Particle Swarm

被引：0
作者：
Liu J. [1 ]
Zheng R. [1 ]
Ding X. [1 ]
Liu H. [2 ]
Yang Z. [1 ]
Wang Z. [1 ]
机构：
[1] College of Automation, Nanjing Univ. of Aeronautics and Astronautics, Nanjing
[2] College of Electronic Sci. and Eng., Southeast Univ., Nanjing
来源：
Gongcheng Kexue Yu Jishu/Advanced Engineering Sciences | 2019年 / 51卷 / 06期
关键词：
Binary quantum behavior particle swarm; Mahalanobis-Taguchi system; Optimization; Variable selection;
D O I：
10.15961/j.jsuese.201900061
中图分类号：
学科分类号：
摘要：
When the standard binary particle swarm is used for the feature selection optimization of Mahalanobis-Taguchi system, the computational speed is slow and the selected features combination of Mahalanobis-Taguchi system is prone to falling into the local optimal solution. To address these problems, a feature selection optimization method of Mahalanobis-Taguchi system based on an improved binary quantum behavior particle swarm was proposed. Firstly, in order to avoid the influence of complex collinearity for the distance metric, the Gram-Schmidt orthogonalization method was used to calculate the Mahalanobis distance value. Through the ROC curve, the optimal threshold point for the system classification was determined. The misclassification rate and the selected variables rate were defined and a multi-objective optimization model was built. Then, an improved quantum behavior particle swarm optimization algorithm was presented to solve the optimization model, which performs binary coding on the particle based on probability. Through the optimized features combination, a new Mahalanobis-Taguchi prediction system was established. Finally, the fetal health diagnosis was carried out. The experimental results showed that the improved quantum behavior particle swarm optimization algorithm could effectively enhance the iterative speed, and the optimized Mahalanobis-Taguchi system had the better prediction accuracy. © 2019, Editorial Department of Advanced Engineering Sciences. All right reserved.
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页码：152 / 158
页数：6
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