计算机应用研究2017，Vol.34Issue(12)：3721-3724,3734,5.DOI:10.3969/j.issn.1001-3695.2017.12.046
改进多分类决策策略的RVM及其在液压泵故障诊断中的应用
Improved multiple classification decision strategy of RVM and its application to fault diagnosis of hydraulic pump
摘要
Abstract
Aiming at the drawbacks of the traditional multi-classification of relevance vector machine using the decision strategy of "maximum number of votes wins" and in order to improve the multi-classification performance of relevance vector machine,this paper improved the multi-classification decision strategy of RVM,and optimized the RVM kernel parameter by LFOA algorithm to establish the classification model.By the evaluation of fitness function,the fruit fly group began a global search for the kernel parameter in the specified range through several iterations.The MATLAB simulation experiment through four UCI standard datasets verifies the effectiveness of the classification model,and the multi-classification decision strategy and proposed optimization method can improve the performance of RVM.Further,it applied this model to the fault diagnosis of hydraulic pump,and achieved a good classification result,which verifies the validity of the proposed classification model.关键词
相关向量机/决策策略/核参数优化/分类模型Key words
RVM/decision strategy/kernel parameter optimization/classification model分类
信息技术与安全科学引用本文复制引用
吕岩,房立清,赵玉龙,齐子元..改进多分类决策策略的RVM及其在液压泵故障诊断中的应用[J].计算机应用研究,2017,34(12):3721-3724,3734,5.基金项目
河北省自然科学基金资助项目(E2016506003) （E2016506003）
