Network community division method based on simulated annealing genetic algorithm

A genetic algorithm and network community technology, applied in the field of network community division, can solve problems such as weak local search ability, unstable division results, and low division efficiency, and achieve fast and effective division, improve local search ability and division stability

Inactive Publication Date: 2012-09-12
XIDIAN UNIV
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AI Technical Summary

Problems solved by technology

Some disadvantages of the current network community structure division method based on genetic algorithm are that the local search ability is weak, the division result is unstable, and the division efficiency is low.

Method used

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  • Network community division method based on simulated annealing genetic algorithm
  • Network community division method based on simulated annealing genetic algorithm
  • Network community division method based on simulated annealing genetic algorithm

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Embodiment Construction

[0027] Combine below figure 1 The specific implementation steps of the present invention are further described in detail.

[0028] Step 1, read in the actual network graph S of a community;

[0029] In the embodiment of the present invention, the network diagram S used is the dolphin community structure diagram in the actual network, such as figure 2 As shown in , it is a network graph of dolphin characteristics obtained by Lusseau after seven years of observation. The connection between any two dolphins in the graph represents the closer relationship between them. The dolphin network is composed of 62 dolphins as nodes in the network, and there are 159 connections between dolphins as edges in the network.

[0030] Step 2, according to the network graph S, generate the adjacency matrix corresponding to the network, and the elements in the adjacency matrix are composed of a ij where i and j represent any two nodes in the network, if node i is connected to node j, then a ij...

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Abstract

The present invention discloses a network community division method based on simulated annealing genetic algorithm, and mainly solves problems of poor search capability and low division efficiency in present genetic algorithm. The network community division method based on simulated annealing genetic algorithm comprises the following realizing steps: (1) reading in a network diagram; (2) generating an adjacent matrix according to the network diagram; (3) initializing genetic algorithm parameters; (4) decoding chromosomes and calculating objective function values; (5) selecting chromosomes with relatively large objective function values to form a parental population; (6) crossing and varying chromosomes and generating new chromosomes to form progeny populations; (7) initializing simulated annealing algorithm parameters and implementing a local search; (8) obtaining a next parental population and performing iteration; (9) determining whether or not the iterative algebra reaches the largest algebra Gmax; if the iterative algebra reaches Gmax, then the iteration is terminated and the chromosome with the largest objective function value is output, and division of every node in the output chromosome is a final division result of nodes in the community. The network community division method based on simulated annealing genetic algorithm has advantages of strong search capability and high accuracy.

Description

technical field [0001] The invention belongs to the computer field, relates to a network community division method, and further relates to the network community division in the small world network technical field, which can be used for network community division. Background technique [0002] With the development of computer technology, complex networks are widely used in various industries. Community is one of the research hotspots in complex network, and the relationship-rich structure composed of nodes of different properties and types in the network is called community. One of the characteristics of a complex network is a community structure in which the relationships within the community are dense and the relationships between different community nodes are sparse. [0003] The division of communities in the network is one of the main problems faced in complex networks. Many methods have been proposed to divide the communities in the network, and one of the research hot...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06N3/12
Inventor 尚荣华焦李成白靖靳超吴建设郑喆坤李阳阳马文萍韩红
Owner XIDIAN UNIV
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