scholarly journals The improved particle swarm breaker fault status parameter optimization of SVM classification

2016 ◽  
Author(s):  
Yihang Sun
Keyword(s):  
Parameter Optimization ◽  
Particle Swarm ◽  
Svm Classification

scholarly journals Parameters Optimization and Application of SVM Based on PCA-Particle Swarm Algorithm

2019 ◽  
pp. 325-330 ◽  
Author(s):  
Qingmi Yang
Keyword(s):  
Parameter Optimization ◽  
Recognition Accuracy ◽  
Recognition Rate ◽  
Particle Swarm ◽  
Optimal Solution ◽  
Principal Component ◽  
Pso Algorithm ◽  
Parameters Optimization ◽  
Support Vector ◽  
Particle Swarm Algorithm

The parameter optimization of Support Vector Machine (SVM) has been a hot research direction. To improve the optimization rate and classification performance of SVM, the Principal Component Analysis (PCA) - Particle Swarm Optimization (PSO) algorithm was used to optimize the penalty parameters and kernel parameters of SVM. PSO which is to find the optimal solution through continuous iteration combined with PCA that eliminates linear redundancy between data, effectively enhance the generalization ability of the model, reduce the optimization time of parameters, and improve the recognition accuracy. The simulation comparison experiments on 6 UCI datasets illustrate that the excellent performance of the PCA-PSO-SVM model. The results show that the proposed algorithm has higher recognition accuracy and better recognition rate than simple PSO algorithm in the parameter optimization of SVM. It is an effective parameter optimization method.

A particle swarm inspired multi-elitist artificial bee colony algorithm for real-parameter optimization

2013 ◽  
Vol 57 (2) ◽  
pp. 493-516 ◽  
Author(s):  
Yi Xiang ◽  
Yuming Peng ◽  
Yubin Zhong ◽  
Zhenyu Chen ◽  
Xuwen Lu ◽  
...  
Keyword(s):  
Parameter Optimization ◽  
Artificial Bee Colony Algorithm ◽  
Artificial Bee Colony ◽  
Particle Swarm ◽  
Real Parameter ◽  
Bee Colony

scholarly journals Improved particle swarm algorithm for hydrological parameter optimization

2010 ◽  
Vol 217 (7) ◽  
pp. 3207-3215 ◽  
Author(s):  
Yan Jiang ◽  
Changmin Liu ◽  
Chongchao Huang ◽  
Xianing Wu
Keyword(s):  
Parameter Optimization ◽  
Particle Swarm ◽  
Particle Swarm Algorithm ◽  
Swarm Algorithm ◽  
Hydrological Parameter
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