计算机应用与软件Issue(6)：192-197,211,7.DOI:10.3969/j.issn.1000-386x.2015.06.048
基于混合粒子群优化 SVM 算法的红斑鳞状皮肤病诊断
DIAGNOSING ERYTHEMATO-SQUAMOUS DISEASE BASED ON HYBRID PARTICLE SWARM OPTIMISATION SVM
摘要
Abstract
The diagnosis of erythemato-squamous disease is a difficult problem in dermatology.In view of this,we propose a hybrid particle swarm optimisation-based support vector machine (SVM)model,namely HAPSO-SVM,for improving the accuracy of erythemato-squamous disease diagnosis.The model takes into account the same important roles on the SVM model played by both the feature selection mechanism and the parameter optimisation,and uses hybrid adaptive particle swarm optimisation (HAPSO)to implement the feature selection mechanism and parameter optimisation simultaneously.Meanwhile,the linear-weighted multi-objective function designed comprehensively considers both the classification accuracy rate and the number of support vectors,therefore improves the accuracy and efficiency of the algorithm.Results show that the proposed algorithm not only achieves small number of support vectors and finds the most related features of erythemato-squamous disease,but also obtains much higher classification accuracy rate,it is proved to be the effective diagnosis model for erythemato-squamous disease.关键词
混合自适应 PSO/红斑鳞状皮肤病诊断/混合模型/支持向量机Key words
Hybrid adaptive PSO/Diagnosis of erythemato-squamous disease/Hybrid model/Support vector machine分类
信息技术与安全科学引用本文复制引用
孙海峰,孙秀玲,齐恩铁,马志广..基于混合粒子群优化 SVM 算法的红斑鳞状皮肤病诊断[J].计算机应用与软件,2015,(6):192-197,211,7.基金项目
吉林省长春市教育厅（吉教科验字［2012］第72号）。 （）
