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Flexible patient rule induction method for optimizing process variables in discrete type
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DOI：10.1016/j.eswa.2007.05.047.png)
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摘要
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This paper deals with process optimization, which establishes the optimal settings of process variables to achieve a better quality. To this end, the patient rule induction method (PRIM), widely used in various application areas, could be adopted. However, the PRIM may fail to provide successful solutions when some process variables are in discrete types. Thus, we propose a new PRIM-like method specially to deal with ordinal discrete variables. For an illustrative purpose, the proposed method is applied to a real steel-making process. Also, performance of the proposed method is compared with the original PRIM through an extensive simulation using artificial data sets. (c) 2007 Elsevier Ltd. All rights reserved.
Keyword:
data mining
ordinal data
process optimization
rule induction
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