Complex network community detecting method based on prior information and network inherent information

Abstract

The invention belongs to the technical field of evolutionary computation and complex network community mining and discloses a complex network community detecting method based on prior information and network inherent information. The method is mainly used for community division of complex networks. The method comprises the steps of establishing a network adjacent matrix, initializing the population by means of adjacent matrix information, conducing preprocessing according to the inherent information of the adjacent matrix to reduce invalid searching, optimizing a modularity function Q, conducting gene interlace operation and mutation operation, using the local search with mutation operator method (LSMM) based on variation and network inherent information, and testing a community division result by means of an evaluation function NMI. According to the method, the community network is detected by fully utilizing prior knowledge and inherent information contained in the network adjacent matrix, an optimal solution is obtained more effectively by means of the LSMM based on variation and network inherent information, and the community structures of a real world network and a synthetic network can be better found compared with an ordinary genetic algorithm.

Description

technical field [0001] The invention belongs to the field of evolutionary calculation and the technical field of complex network community mining, and relates to a method for community division of a network using an evolutionary calculation method in the field of complex network, in particular to a complex network community detection method based on prior information and inherent network information. Background technique [0002] There are various complex networks in the real world, such as dense transportation networks and power networks in cities; ecological networks in nature; and online relationship networks between people in human society. With the increasing development of society and technology, human beings need to have a better understanding of various natural and artificial complex networks. Therefore, complex network research has become one of the most important interdisciplinary research fields. Community structure is a common property of many complex networks i...

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Problems solved by technology

[0003] The purpose of the present invention is to overcome the poor network division results caused by the inability of the traditional genetic algorithm to make good use of the inherent information contained in the original network, and the traditional genetic algorithm has too many invalidities because its search range is the entire feasible domain space. Search, and the problem that the traditional genetic algorithm runs unstable every time

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