摘要
将主成分分析(PCA)和优化支持向量机结合,提出了一种适用小样本空间的网络化制造资源优化配置模型——PCA-OSVM模型。该模型以传统网络化制造系统中资源配置指标为基础,通过主成分分析,简化了输入变量,并利用OSVM作为判别企业资源状态的工具,可以在产品全生命周期中的每个环节选中一个或多个企业参与,避免了传统算法模型在解决优化配置问题上的缺陷。算例结果表明,所提出的模型能有效提高优化配置方案的可行性,为网络化制造资源优化配置的在线实施提供了方便。
This paper propeses a new method： PCA-OSVM model which is composed of PCA and OSVM to optimize the allocation of networked manufacturing resources through resources allocation data. The model is fit for company in the small sample space. It uses PCA to predigest the input vector and uses OSVM to judge the statement of the company resources. With the model, one or more enterprises could he selected in every process in full lifecycle of product, and the defects in resolving optimal configuration with traditional algorithm model could be omitted. The application case proved that the proposed method can improve the feasibility of the program in optimal configuration, and it is suitable for on-line resource optimal configuration control for networked manufacturing.
出处
《装备制造技术》
2009年第10期101-103,共3页
Equipment Manufacturing Technology
关键词
主成分分析
优化支持向量机
网络化制造
优化配置
principal component analysis
optimized support vector machine
networked manufacturing
optimal configuration
