Density Peaks Clustering Based on Multiple Distance Measures for Manufacturing Process
文献类型：会议论文
| 作者 | Li S(李帅) ; Gao SY(高诗莹); Zhou XF(周晓锋)
|
| 出版日期 | 2016 |
| 会议名称 | 2016 IEEE International Conference on Information and Automation, IEEE ICIA 2016 |
| 会议日期 | July 31 - August 4, 2016 |
| 会议地点 | Ningbo, China |
| 关键词 | Density peaks clustering Distance measure Mode division Manufacturing process |
| 页码 | 1143-1148 |
| 通讯作者 | 李帅 |
| 中文摘要 | Data analysis and processing of manufacturing process is significant to ensure the stable production safety, maintain quality stabilization, and optimize production profit. Practical manufacturing process often has complex characteristics, such as multimode, nonlinearity, etc. Mode division can divide manufacturing process into multiple modes and is useful for subsequent process monitoring and scheduling optimizing. In this paper, density peaks clustering (DPC) based on multiple distance measures is used for mode division in manufacturing process. Multiple distance measures for computing the local density and minimum distance between the point and any other point with higher density in DPC are compared and analyzed. To illustrate the effectiveness of the clustering method for mode division in manufacturing process, experiments are developed based on penicillin fermentation process and practical foods industrial production process. Experimental results verify the feasibility and efficiency of the clustering method for mode division in manufacturing process. |
| 收录类别 | EI |
| 产权排序 | 1 |
| 会议录 | Proceedings of the IEEE International Conference on Information and Automation
 |
| 会议录出版者 | IEEE |
| 会议录出版地 | New York |
| 语种 | 英语 |
| ISBN号 | 978-1-5090-4102-2 |
| 源URL | [http://ir.sia.cn/handle/173321/19484]  |
| 专题 | 沈阳自动化研究所_数字工厂研究室 |
| 推荐引用方式 GB/T 7714 | Li S,Gao SY,Zhou XF. Density Peaks Clustering Based on Multiple Distance Measures for Manufacturing Process[C]. 见:2016 IEEE International Conference on Information and Automation, IEEE ICIA 2016. Ningbo, China. July 31 - August 4, 2016. |
入库方式： OAI收割
来源：沈阳自动化研究所
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