Complex network community mining method based on improved genetic algorithm

Abstract

The invention discloses a complex network community mining method based on an improved genetic algorithm and belongs to the technical field of complex network community mining method research. The complex network community mining method based on the improved genetic algorithm uses the improved genetic algorithm based on clustering and double population thought fusion to mine communities in a complex network. The complex network community mining method based on the improved genetic algorithm uses a normalization common information similarity standard as the standard for measuring the similarity between individuals in the population and fuses the clustering and double population thought. The complex network community mining method based on the improved genetic algorithm includes that introducing the clustering thought, using a minimum spanning tree clustering method to classify the population, introducing the double population thought, and determining the main type and auxiliary type for the clustering. The main type maintains the population evolution direction to get close to the optimal solution of an objective function; the auxiliary type is mainly used for duly providing diversity for the main type so as to enable the main type to be capable of coming out to search the other solution space to realize the complex network community mining when the main type is located at the local optimum.

Description

technical field [0001] The invention belongs to the technical field of complex network community mining method research, and specifically uses an improved genetic algorithm based on the fusion of clustering and dual-population ideas to mine communities in complex networks. A new approach to community mining in complex networks with dual-population thought fusion methods. Background technique [0002] In the real world, many complex systems exist in the form of networks, or can be abstracted into complex networks. The study of complex networks has become a research hotspot in many fields. Many systems in the real world can be seen as the result of the interaction of many subsystems. A complex network is an abstraction of a complex system. If the vertices in a complex network are regarded as individuals in a complex system, then the edges in a complex network can be regarded as the interconnections between individuals in a complex system. Complex networks simplify the syste...

AI Technical Summary

Problems solved by technology

[0006] Gong et al. proposed a GA-based community mining algorithm—MA (memetic algorithm), which is prone to local optima and difficult to find a global optimal solution. Ronghua Shang proposed a method based on modularity and improved genetic algorithm. Community Discovery Algorithm (MIGA) is used to solve this problem. However, the MIGA algorithm needs prior knowledge - the number of communities in complex networks, which makes the algorithm's performance in dealing with complex network community mining problems with unknown numbers of communities reduced.

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