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Title:
an approximate approach to constraint solving in soft sensing
Author: Yang Tian ; Liao Zaifei ; Lu Xinjie ; Wang Hongan
Source: Proceedings of the ACM Symposium on Applied Computing
Conference Name: 24th Annual ACM Symposium on Applied Computing, SAC 2009
Conference Date: 37323
Issued Date: 2009
Conference Place: Honolulu, HI, United states
Keyword: Granular computing ; Measurements ; Sensors
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
Sponsorship: ACM SIGAPP
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.
Content Type: 会议论文
URI: http://ir.iscas.ac.cn/handle/311060/8416
Appears in Collections:人机交互技术与智能信息处理实验室_会议论文

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Recommended Citation:
Yang Tian,Liao Zaifei,Lu Xinjie,et al. an approximate approach to constraint solving in soft sensing[C]. 见:24th Annual ACM Symposium on Applied Computing, SAC 2009. Honolulu, HI, United states. 37323.
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