ISCAS OpenIR  > 人机交互技术与智能信息处理实验室
an approximate approach to constraint solving in soft sensing
Yang Tian; Liao Zaifei; Lu Xinjie; Wang Hongan
2009
Conference Name24th Annual ACM Symposium on Applied Computing, SAC 2009
SourceProceedings of the ACM Symposium on Applied Computing
Conference Date37323
Conference PlaceHonolulu, HI, United states
Publish PlaceUnited States
ISBN9781605581668
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 AbstractSoft 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.
KeywordGranular Computing Measurements Sensors
SponsorshipACM SIGAPP
Content Type会议论文
URIhttp://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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