摘要
本文简要描述了关联规则问题及二进制粒子群优化算法(Binary Particle Swarm Optimization,BPSO),提出了一种基于粒子群优化算法的关联规则挖掘算法。仿真试验研究了关联规则在股市走势中的应用,选取相对强弱指标RSI,收集交易数据进行实证分析,得出若干条有用的关联规则。
Association rules and binary particle swarm optimization is described in this paper, and an algorithm based on particle swarm optimization algorithm is proposed for mining association rules. Simulation experiments were conducted to study the application of association rules in the stock market trend, the Relative Strength Index RSI is selected, and the transaction data is collected for empirical analysis, in the end, several useful association rules is proposed. The simulation results show that running time of the algorithm is shorter, and resulting in fewer and more effective rules.
出处
《信息技术与信息化》
2009年第3期85-87,共3页
Information Technology and Informatization
基金
国家自然科学基金重大项目(No.60873058
No.60743010)
山东省自然科学基金重大项目(Z2007G03)
"泰山学者"建设工程专项经费资助项目
山东省教育厅计划项目
