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Multi-target brain storm community detection method based on novelty search

A technology of brainstorming and detection methods, applied in the field of multi-objective brainstorming community detection based on novelty search, can solve the problem of maintaining population diversity and fall into local optimum, so as to enhance global search ability, avoid premature convergence, and achieve full optimization. effect of ability

Pending Publication Date: 2020-12-25
XIAN UNIV OF POSTS & TELECOMM
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Problems solved by technology

[0007] The present invention provides a multi-objective brainstorming community detection method based on novelty search, which solves the shortcoming of falling into local optimum while maintaining population diversity in multi-objective optimization problems in the prior art

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  • Multi-target brain storm community detection method based on novelty search
  • Multi-target brain storm community detection method based on novelty search
  • Multi-target brain storm community detection method based on novelty search

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Embodiment Construction

[0039] The idea, specific structure and technical effects of the present invention will be clearly and completely described below in conjunction with the actual flow and accompanying drawings, so as to fully understand the purpose, features and effects of the present invention.

[0040] This embodiment provides a novelty search-based multi-target brainstorming community detection method, specifically including:

[0041] Step 1: read the input network, and use the LAR code to initialize the algorithm;

[0042] Step 2 Initialize the population: set the initial population size popnum, use LAR code to randomly generate popnum initial solutions s, and calculate the NRA and RC values ​​of s according to formula 1;

[0043] 2.1 The encoding method based on neighbor nodes is mainly divided into four steps: determine the neighbor set of each node, select each node neighbor, construct the encoding list and the decoding process. Taking Figure 2 as an example, the process is as follows: ...

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Abstract

The invention relates to a multi-target brain storm community detection method based on novelty search. The method comprises the following steps: reading an input network; initializing a population; updating the external archive EP by utilizing all solutions in the population; disturbance of elite individuals; obtaining a novelty solution; randomly selecting individuals C1 and C2 from an externalarchive and a current population; randomly selecting individuals C1 and C2 from an external archive and a novelty solution; calculating NRA and RC values of the new population, and updating an external archive; when the external archive Q times is not updated or reaches the iteration frequency p, executing a restart operation, and returning to the step 2; judging whether a termination condition ismet or not, if so, calculating a modularity Q value and a maximum normalized mutual information NMI value of the external archive, and otherwise, returning to the step 3; and outputting a group of divided network structures. Premature convergence can be effectively avoided, and the global search capability of individuals is enhanced; the diversity of populations can be maintained; and early-maturing convergence can be effectively avoided.

Description

technical field [0001] The invention relates to the technical field of complex network community detection, in particular to a multi-target brainstorming community detection method based on novelty search. Background technique [0002] It is of great significance to detect the community structure in a complex network, because researchers have found that the community structure of a complex network reflects the distribution and interconnection of each clustered small network in a large network, and the connections between the points in these small networks The small network is sparsely connected with the external points, and the internal points of these small networks have the same function and hidden information. Therefore, detecting the community structure in a complex network can help to better understand the organizational structure of the network system, and at the same time can dig out the function of the organizational structure of the network system. [0003] Communi...

Claims

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Application Information

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IPC IPC(8): G06Q10/06G06Q10/04G06Q50/00G06N3/00
CPCG06N3/006G06Q10/04G06Q10/06395G06Q50/01
Inventor 潘晓英王佳李红叶廉佳
Owner XIAN UNIV OF POSTS & TELECOMM
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