Title: | an algorithm for uncertain data reconciliation in process industry |
Author: | Zaifei Liao
; Tian Yang
; Xinjie Lu
; Hongan Wang
|
Source: | 2009 WRI World Congress on Computer Science and Information Engineering, CSIE 2009
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Conference Name: | 2009 WRI World Congress on Computer Science and Information Engineering, CSIE 2009
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Conference Date: | March 31,
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Issued Date: | 2009
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Conference Place: | Los Angeles, CA, United states
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Keyword: | Computer science
; Industrial applications
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Publish Place: | United States
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ISBN: | 9780769535074
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Department: | (1) Intelligence Engineering Lab., Institute of Software, Chinese Academy of Sciences, Beijing, 100190, China
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English Abstract: | This 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. |
Content Type: | 会议论文
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URI: | http://ir.iscas.ac.cn/handle/311060/8490
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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: |
Zaifei Liao,Tian Yang,Xinjie Lu,et al. an algorithm for uncertain data reconciliation in process industry[C]. 见:2009 WRI World Congress on Computer Science and Information Engineering, CSIE 2009. Los Angeles, CA, United states. March 31,.
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