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| an approximate approach to constraint solving in soft sensing | |
| Yang Tian; Liao Zaifei; Lu Xinjie; Wang Hongan | |
| 2009 | |
| Conference Name | 24th Annual ACM Symposium on Applied Computing, SAC 2009 |
| Source | Proceedings of the ACM Symposium on Applied Computing |
| Conference Date | 37323 |
| Conference Place | Honolulu, HI, United states |
| Publish Place | United States |
| ISBN | 9781605581668 |
| Department | (1) Graduate University, Chinese Academy of Sciences, Beijing, China; (2) Institute of Software, Chinese Academy of Sciences, Beijing, China; (3) State Key Lab. of Computer Science, Institute of Software, Chinese Academy of Sciences, Beijing, China |
| English Abstract | Soft sensing is usually presented as a constraint solving problem. In a manufacturing context, traditional methods of soft sensing have to face challenges in robustness and efficiency. In this paper, we proposed a granular-based approach to constraint solving for soft sensing. In our method, we first construct a granular-based soft sensing model, then estimate bounds of each granule, and finally solve this granulated problem with a smaller size. According to our analysis, this method is robust and efficient. Copyright 2009 ACM. |
| Keyword | Granular Computing Measurements Sensors |
| Sponsorship | ACM SIGAPP |
| Content Type | 会议论文 |
| URI | http://ir.iscas.ac.cn/handle/311060/8416 |
| Collection | 人机交互技术与智能信息处理实验室 |
| Recommended Citation GB/T 7714 | Yang Tian,Liao Zaifei,Lu Xinjie,et al. an approximate approach to constraint solving in soft sensing[C]. United States,2009. |
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