| 基于支持向量基的关联规则挖掘及其在模拟移动床PX吸附分离过程中的应用 |
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| 引用本文： | 张英,苏宏业,褚健. 基于支持向量基的关联规则挖掘及其在模拟移动床PX吸附分离过程中的应用[J]. 中国化学工程学报, 2005, 13(6): 751-757 |
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| 作者姓名： | 张英 苏宏业 褚健 |
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| 作者单位： | National Laboratory of Industrial Control Technology, Institute of Advanced Process Control, Zhejiang University, Hangzhou 310027, China |
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| 基金项目： | Supported by the National Natural Science Foundation of China （No. 60421002）, National 0utstanding Youth Science Foundation of China （No. 60025308） and the New Century 151 Talent Project of Zhejiang Province. |
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| 摘 要： | In this paper, a novel data mining method is introduced to solve the multi-objective optimization problems of process industry. A hyperrectangle association rule mining （HARM） algorithm based on support vector machines （SVMs） is proposed. Hyperrectangles rules are constructed on the base of prototypes and support vectors （SVs） under some heuristic limitations. The proposed algorithm is applied to a simulated moving bed （SMB） paraxylene （PX） adsorption process. The relationships between the key process variables and some objective variables such as purity, recovery rate of PX are obtained. Using existing domain knowledge about PX adsorption process, most of the obtained association rules can be explained.
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| 关 键 词： | 支持向量 关联规则挖掘 模拟移动床 PX 吸附分离 对二甲苯 |
| 收稿时间： | 2005-01-05 |
| 修稿时间： | 2005-01-052005-08-11 |
Association Rules Mining Based on SVM and Its Application in Simulated Moving Bed PX Adsorption Process |
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| ZHANG Ying,SU Hongye,CHU Jian. Association Rules Mining Based on SVM and Its Application in Simulated Moving Bed PX Adsorption Process[J]. Chinese Journal of Chemical Engineering, 2005, 13(6): 751-757 |
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| Authors: | ZHANG Ying SU Hongye CHU Jian |
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| Affiliation: | National Laboratory of Industrial Control Technology, Institute of Advanced Process Control, Zhejiang University,Hangzhou 310027, China;National Laboratory of Industrial Control Technology, Institute of Advanced Process Control, Zhejiang University,Hangzhou 310027, China;National Laboratory of Industrial Control Technology, Institute of Advanced Process Control, Zhejiang University,Hangzhou 310027, China |
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| Abstract: | In this paper, a novel data mining method is introduced to solve the multi-objective optimization problems of process industry. A hyperrectangle association rule mining (HARM) algorithm based on support vector machines (SVMs) is proposed. Hyperrectangles rules are constructed on the base of prototypes and support vectors (SVs) under some heuristic limitations. The proposed algorithm is applied to a simulated moving bed (SMB) paraxylene (PX) adsorption process. The relationships between the key process variables and some objective variables such as purity, recovery rate of PX are obtained. Using existing domain knowledge about PX adsorption process, most of the obtained association rules can be explained. |
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| Keywords: | multi-object optimization simulated moving bed support vector machines rule extraction clustering |
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