Temporal and Spatial Association Rules Strong Mining Algorithm Based on Hierarchical Reasoning Parameters

Abstract

Such problems as premature convergence and local optimal solution universally exist in the application of traditional genetic algorithm to the association rules mining, so a lot of time is needed for extracting the useful strong association rules. In order to conquer these disadvantages, the adaptive variation rate is introduced in this paper and the method for the operator selection during the genetic process is improved in order to specifically improve the traditional genetic algorithm, and the improved association rules mining method is used to analyze the power transformation equipment defect data. The example comparison shows that the improved genetic algorithm can significantly reduce the rule discovery calculation complexity and improve the association rules mining efficiency.