Abstract:  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.

Key words: association rules, Apriori algorithm, textile raw materials, expense cost alert