Non-redundant Multilayer Mining Algorithm for Multidimensional Multilayer Data

According to the traditional mining method has been the realization process of complex problems, proposed multi-dimensional data based on immune genetic algorithm for mining non redundant cross layer, first through the Rodgers regression function to collect the multi-dimensional data, and through the consistency of the multi-dimensional data source and target domain to classify the multi-dimensional data, on the basis of through the analysis, the basic idea of immune genetic algorithm to realize the multi-dimensional data mining non redundant cross layer, determine the encoding scheme and the fitness function, and through genetic manipulation and group updates, complete multi-dimensional data based on immune genetic algorithm for mining non redundant cross layer. The experimental results show that the proposed algorithm for multi-dimensional data mining non redundant cross layer, the implementation process is relatively simple, less impact on the computer network running speed, wide application, to provide new ideas for the development of this field.