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浙江大学学报(工学版)
J4  2009, Vol. 43 Issue (12): 2203-2207    DOI: 10.3785/j.issn.1008-973X.2009.12.013
工业工程与制造业信息化     
基于免疫离散粒子群算法的调度属性选择
叶建芳,潘晓弘,王正肖,唐任仲
（浙江大学 现代制造工程研究所,浙江省先进制造技术重点研究实验室,浙江 杭州 310027）
Scheduling feature selection based on immune binary partial swarm optimization
YE Jian-fang, PAN Xiao-hong, WANG Zheng-xiao, TANG Ren-zhong
(Institute of Manufacturing Engineering, Zhejiang Province Key Laboratory of Advanced Manufacturing Technology, Zhejiang University, Hangzhou 310027,China)
 全文: PDF(595 KB)   HTML
摘要：

为了解决制造系统状态描述的问题，需要从众多的属性中择优选择合适的属性集合，以便降低属性的冗余度，减少计算量.提出了用免疫离散粒子群算法进行属性选择的方法，给出了属性选择的粒子表达、适应度函数的定义以及免疫机制.通过仿真实验给出了描述制造系统状态的入选属性集合，并进行了对比实验，将待选属性集合、入选属性集合和落选属性集合作为支持向量机的输入，来比较3种情况下分类的准确性和验证属性选择的有效性.实验结果表明，经过选择后的属性集合分类准确性大大高于另外两种情况，从而实现对制造系统状态的有效识别，为在不同的状态下采取合适的调度规则
建立了基础.
Abstract:

A large number of properties need to be selected into the appropriate attributes sets to describe the manufacturing system state in order to reduce the redundancy of attributes and reduce the computational complexity. A feature selection method was proposed based on immune binary partial swarm optimization. Particle expression of feature selection, definition of fitness function and immune mechanisms were given. The selection results were presented through numerical simulation. A comparative experimentation was designed to testify the effectiveness of the method. Three attribute sets: candidate sets, selected sets and deselected sets were used as the input of support vector machine respectively. Results demonstrate that the classification accuracy of selected sets is greatly better than the other. Then the system state can be effectively recognized and the appropriate rule can be adopted for the corresponding manufacturing system state.
出版日期: 2010-01-16
:  TP 278  
基金资助:

国家自然科学基金资助项目（50675201）;浙江省科技计划资助项目（2006C11237）.
通讯作者: 王正肖,男,副教授.     E-mail: wangzhengxiao@zju.edu.cn
作者简介: 叶建芳（1980-）,女,浙江建德人,博士生,主要从事生产管理、作业调度的研究.
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引用本文:

叶建芳, 潘晓弘, 王正肖, 等. 基于免疫离散粒子群算法的调度属性选择[J]. J4, 2009, 43(12): 2203-2207.

XIE Jian-Fang, BO Xiao-Hong, WANG Zheng-Xiao, et al. Scheduling feature selection based on immune binary partial swarm optimization. J4, 2009, 43(12): 2203-2207.

链接本文:

http://www.zjujournals.com/eng/CN/10.3785/j.issn.1008-973X.2009.12.013    或    http://www.zjujournals.com/eng/CN/Y2009/V43/I12/2203


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