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- W2348544439 abstract "To construct an expert system,knowledge acquisition is the bottleneck problem,and the key to scientific decision-making is accurate inference knowledge.In this paper,it will use rough sets theory to attribute value reduction algorithms that filter and remove the redundant condition attribute value of decision-making table's each record.First,research the theoretical basis of attribute value reduction,including knowledge representation and knowledge reduction and core both.Then,research knowledge acquisition ways and knowledge acquisition processes.Third,research the attribute value reduction algorithms,through the description of two definitions the reduction algorithms is given the 5 steps.Finally,take the city logistics center location as example,use attribute value reduction algorithms and its steps for the value of decision table attribute reduction.The results show that attribute value reduction achieves the most streamlined decision-making table,highlighting the key attributes and key decision-making of property value." @default.
- W2348544439 created "2016-06-24" @default.
- W2348544439 creator A5075053838 @default.
- W2348544439 date "2013-01-01" @default.
- W2348544439 modified "2023-09-23" @default.
- W2348544439 title "An Attribute Value Reduction Algorithm of Expert System Knowledge Acquisition" @default.
- W2348544439 hasPublicationYear "2013" @default.
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