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| The Attribute Reduction of Regional Logistics Demand Based on Rough Set Theory |
| Guoxiang Li, Guoen Xia, Xin Peng |
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Abstract This paper proposes a novel approach for logistics data analysis. A
large number of four regions historical data was collected by
building a complete demand influencing factors of regional logistics
system. Through using the minimum entropy discrete the condition
attributes and using genetic algorithm to construct decision table,
we develop a mechanism to generate Attribute Reduction. The
validation of the proposed approach is illustrated on various data
sets and experiment showed that it can efficiently avoid the data
choice impacted by the subjective factor of qualitative analysis and
the resulting decision rules table can make a certain degree
prediction of regional logistics.
DOI: 10.12733/jics20101729
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