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Optimal setting for coking flue gas denitriation process indices based on PCR-multi-case fusion
Li YN(李亚宁)1,2; Wang XL1; Bai XW1,2; Tan J1; Liu CB1,2
2017-06
会议名称3th IEEE International Conference on Cybernetics
页码1-7
会议日期21-23 June, 2017
会议地点Exeter
摘要In the operation process of the flue gas desulfurization and denitriation, the concentration of ozone and denitriation solution are the most important operating parameters. The two parameters are set manually at the present, where exist great subjectivity and randomness, causing great waste of energy. However, the complex mechanism, serious nonlinear and interference of the process make it difficult to establish precise mathematical model to calculated set-points. In order to solve this problem, a method based on case based reasoning is proposed to optimize the set-points of coking gas denitriation process. The case construction, case retrieval, case reuse, case modification and storage are discussed in detail, meanwhile, noticed the defect that the single feature description of current working condition may result in biased solutions of traditional case reuse, a case reuse method based on principal component regression-multiple case fusion is proposed. This approach has been simulated and applied in a coking plant with its effectiveness and superiority actually proved.
关键词Coking Flue Gas Denitration(Dn) Case-based Reasoning(Cbr) Principal Component Regression(Pcr)
收录类别EI
文献类型会议论文
条目标识符http://ir.ia.ac.cn/handle/173211/21183
专题综合信息系统研究中心
作者单位1.中国科学院自动化研究所
2.中国科学院大学
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GB/T 7714
Li YN,Wang XL,Bai XW,et al. Optimal setting for coking flue gas denitriation process indices based on PCR-multi-case fusion[C],2017:1-7.
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