Control Chart Patterns Recognition based on DAG-SVM
文献类型：会议论文
| 作者 | Xiao ZB(肖忠保) ; Chen SH(陈书宏)
|
| 出版日期 | 2015 |
| 会议名称 | 6th International Conference on Manufacturing Science and Engineering (ICMSE) |
| 会议日期 | November 28-29, 2015 |
| 会议地点 | Guangzhou, PEOPLES R CHINA |
| 关键词 | DAG SVM PSO |
| 页码 | 1056-1062 |
| 中文摘要 | Statistical process control charts have been widely utilized in manufacturing processes for determining whether a process is run in its intended mode or in the presence of unnatural patterns, it's a multi-class classifier problem. Effective approaches to recognize control chart patterns is essential for a manufacturing process to maintain high-quality products. This paper we use the Directed Acyclic Graph(DAG) tree learning architecture, which combines many two-class classifiers together to solve the multi-class classifier problem. For each node we chose the support vector machine(SVM) using a particle swarm optimization(PSO) algorithm to optimize the parameter of the SVM kernel function. Here the PSO not only takes the kernel function parameters as variables but also the feature vector of the SVM to optimize. Simulation results show the propose algorithm achieves a high recognition accuracy and solve the unable recognition area. |
| 收录类别 | CPCI（ISTP） |
| 产权排序 | 1 |
| 会议录 | PROCEEDINGS OF THE 2015 6TH INTERNATIONAL CONFERENCE ON MANUFACTURING SCIENCE AND ENGINEERING
 |
| 会议录出版者 | ATLANTIS PRESS |
| 会议录出版地 | PARIS |
| 语种 | 英语 |
| ISSN号 | 2352-5401 |
| ISBN号 | 978-94-6252-137-7 |
| WOS记录号 | WOS:000388457800193 |
| 源URL | [http://ir.sia.cn/handle/173321/19490]  |
| 专题 | 沈阳自动化研究所_智能检测与装备研究室 |
| 推荐引用方式 GB/T 7714 | Xiao ZB,Chen SH. Control Chart Patterns Recognition based on DAG-SVM[C]. 见:6th International Conference on Manufacturing Science and Engineering (ICMSE). Guangzhou, PEOPLES R CHINA. November 28-29, 2015. |
入库方式： OAI收割
来源：沈阳自动化研究所
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