GSP算法在企业动态成本预测中的应用

Chengguan Xiang, Shihuan Xiong
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引用次数: 6

摘要

利用序列模式挖掘的结果,构建一个投影数据库,减少了整个数据库的扫描次数和候选序列的创建,可以弥补GSP算法的不足。这样,提高了采矿效率;满足了海量数据对计算速度的要求。便于从海量数据中查找合适的成本信息,进而进行成本分析和成本预测。将改进的时间序列模式应用于企业成本预测表明,这种计算系统可以有效地提高成本预测的准确性和及时性。
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The GSP algorithm in dynamic cost prediction of enterprise
By making use of the previous result of sequential pattern mining, a projection database will be build to help decrease the scanning times of the whole database and the creation of the candidate sequence, which can make up for the weakness of the GSP. In this way, the mining efficiency is enhanced; the demand of the computing speed of the massive data is satisfied. So it is convenient to search for the right cost information from the massive data and then to proceed with cost analysis and cost prediction. The application of the improved time sequential pattern to the cost prediction in the enterprises demonstrates that this kind of computing system can enhance the accuracy and promptness of cost prediction effectively.
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