ISCAS OpenIR  > 人机交互技术与智能信息处理实验室
an algorithm for uncertain data reconciliation in process industry
Zaifei Liao; Tian Yang; Xinjie Lu; Hongan Wang
2009
Conference Name2009 WRI World Congress on Computer Science and Information Engineering, CSIE 2009
Source2009 WRI World Congress on Computer Science and Information Engineering, CSIE 2009
Conference DateMarch 31,
Conference PlaceLos Angeles, CA, United states
Publish PlaceUnited States
ISBN9780769535074
Department(1) Intelligence Engineering Lab., Institute of Software, Chinese Academy of Sciences, Beijing, 100190, China
English AbstractThis paper proposes an uncertain data reconciliation algorithm for Process Industry. First of all, the dynamic Event Dependency Graph is defined to abstract the problem. Taking into account the scale of the industry, a granularity partition algorithm relied on event detection is presented. In the following for the purpose of data prediction to improve the precision of the predicted value of the measured data, an improved Least Squares Support Vector Machine (LSSVM) model based on relative error is proposed. On the basis of the above, we present our data reconciliation algorithm by constructing a constraint model to achieve the goal of on-line/off-line data reconciliation. The practical industrial applications proved the efficiency and performance of the algorithm. © 2008 IEEE.
KeywordComputer Science Industrial Applications
Content Type会议论文
URIhttp://ir.iscas.ac.cn/handle/311060/8490
Collection人机交互技术与智能信息处理实验室
Recommended Citation
GB/T 7714
Zaifei Liao,Tian Yang,Xinjie Lu,et al. an algorithm for uncertain data reconciliation in process industry[C]. United States,2009.
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