基于改进的Apriori算法和遗传算法的股市挖掘模型

Mining Model of Stock Market Based on Improved Apriori Algorithm and Genetic Algorithm

经典的关联规则挖掘算法——Apriori算法需要多次扫描数据库和过多的IO接口操作,费时费力。采用空间换时间的思路对其进行了改进。同时因为Apriori算法挖掘出的关联规则存在误导规则和弱关联规则等问题,而能够进行全局求解的遗传算法正好能够解决该问题,使用加入理解度概念的遗传算法对用改进的Apriori算法挖出的关联规则再次挖掘。之后,这种复合模型被应用到我国现阶段股市中,挖掘出了大量、实用的关联规则,对买卖股票起着良好的指导作用。

When Apriori algorithm is applied,scanning the database repeatedly and excessive IO interface operation require much time and energy.Apriori algorithm was improved by the thinking of using space instead of time.Genetic algorithm with the capability of solving the global can solve the problems that exist in the mining association rules based on Apriori algorithm,such as misleading rules and weak association rules.Genetic algorithm added with the understanding concept was used in the mining association rules by improved Apriori algorithm.This composite model was applied to the stock market in China at present by providing a lot of practical association rules which were good guidance for buying and selling stocks.