基于关联规则Apriori算法的纺织原料成本预警

Textile Raw Material Cost Warning Based on Apriori Algorithm of Association Rules

为了解决现有预警方法存在预警精度与成功率较低的问题,提出一种基于关联规则Apriori算法的纺织原料成本预警方法。分析纺织原料成本组成,主要包括原料成本、电费成本、薪资成本、其他费用支出成本、运输和装卸成本以及期间成本,并研究纺织原料成本管理内容。构建纺织业成本预警指标体系,运用灰度关联分析方法精准挖掘预警数据序列;并采用Apriori算法计算预警数据的最大频繁项集,通过置信度结果的计算,完成纺织原料成本预警。实验结果表明,本文方法的预警精度较高,预警耗时较短,并且具有较高的预警成功率。

In order to solve the problems of low accuracy and success rate of existing early warning methods,this paper proposes a textile raw material cost early warning method based on the Apriori algorithm of association rules.The composition of textile raw material cost is analyzed,including raw material cost,electricity cost,salary cost,other expenses,transportation and loading and unloading cost and period cost.The content of textile raw material cost management is studied.The cost early warning index system of textile industry is established,and the gray correlation analysis method is used to accurately mine the early warning data sequence.The Apriori algorithm is used to calculate the maximum frequent item set of the warning data,and the textile raw material cost warning is completed through the calculation of the confidence results.The experimental results show that the method proposed in this paper has high accuracy,short time-consuming and high success rate of early warning.