Methods For Cigarette Formula Maintenance Based On Association Rule Mining

With the impact of economic globalization,the competition of tobacco industry is increasingly fierce.The demand of maintenance and development of the cigarette products is higher and higher.In our country,a lot of expert experience and formula experiment are needed in the production process of cigarette formulation,so the cigarette staffs need strict technical accumulation and experience,at the same time a large number of production tests will cause excessive waste of raw materials.Obviously,the efficiency of the traditional method is low and has poor stability.Based on a large amount of historical data accumulated in the process of enterprise production,enterprises urgently need to optimize the formula maintenance,and to find a saving,simplified and efficient solution for maintenance.In the process of the cigarette formulation maintenance,cigarette enterprises presently only rely on experts to carry on the manual evaluation of the tobacco leaf..In the process of constantly smoking,they wil adjust the proportion of various kinds of tobacco leaves.However,the problem of this method is that the workload is huge,repetive,time-consuming and tobacco-wasting.Enterprises need a system that can automatically recommend the formulation based on historical data.Based on the formula data provided by H group,this thesis carries out the research on the correlation between the formula attribute analysis,the rule mining and formula maintenance.The major work includes the following four parts:(1)According to the data of formula and single cigarette provided by the H company,this thesis carries on the data preprocessing and fills the missing values in the data.By using SPSS software,the thesis explores the characteristics of cigarette formula between chemical elements and attributes,then compares the relationship of regression.Experiments support the internal relationship in the formula.(2)Based on the study of formula knowledge,a lot of abstract expert experience can be found.By using the method of association rules,some implicit compatibility rules and single cigarette coexistence relationships can be extracted.Because the number of rules is big,the rules are reduced for facilitating use.(3)Based on the association rule mining,the heuristic cigarette formula maintenance method is developed based on frequent itemsets and similarity method.It can be used to express the expert experience,dynamically allocate the quantity of the unblended cigarettes,and realize the intelligence of the cigarette formula maintenance.(4)On the basis of the above work and combining with the enterprise needs,an computer-aided decision-support system of cigarette optimization using Matlab GUI is developed.Three modules are built in the system.The first module is mining rules about formula,the second is heuristic maintenance and the last is formula indicators prediction.Dataset from H group were used to verify the deveoped algorithms.