Improved Genetic Algorithm Based on Simulated Annealing and Quantum Computing Strategy for Mining Association Rules

摘要

Association rules mining is an importantcontent in data mining. It can discover the relations ofdifferent attributes by analyzing and disposing datawhich is in database. This paper proposes a novel datamining algorithm to enhance the capability ofexploring valuable information from databases withcontinuous values. The algorithm combines withquantum-inspired genetic algorithm and simulatedannealing to find interesting association rules. Thefinal best sets of membership functions in all thepopulations are then gathered together to be used formining association rules. The experiment resultdemonstrates that the proposed approach couldgenerate more association rules than other algorithms.