A New Spatial Association Rules Mining Method Based on Immune Algorithms

On the basis of analyzing the now-generally-used spatial association rules algorithm,aiming at the shortage of the very large database spatial association rules mining,a spatial association rules mining algorithm based on immune algorithms is proposed.This algorithm makes use of the immune recognition mechanism,immune memory characters and clonal selection characters.In the process of spatial association mining,spatial association rules are regarded as the antigens,candidate itemsets are looked upon as the antibodies.The spatial association rules are stored in memory,and speed of mining spatial association rules is accelerated.We take the incidence relation of special data of pole and tower fault as an example,to verify the algorithm.Experiment results show that the proposed algorithm is effective.The algorithm is able to be more quickly and efficiently search in the whole global,and extremely be used for the mining spatial association rules to very large database.