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Multi-agent data mining method based on artificial immunity network

An artificial immune network and multi-agent technology, applied in the field of multi-agent data mining based on artificial immune network, can solve problems such as poor description of natural mechanisms, single-angle simulation, difficulties, etc., and improve dynamic analysis capabilities , Improving the clustering accuracy and improving the effect of classification accuracy

Inactive Publication Date: 2015-05-13
HUAQIAO UNIVERSITY
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AI Technical Summary

Problems solved by technology

However, the biological immune system is a complex dynamic adaptive system, and it is very difficult to completely simulate the mechanism of the biological immune system
At present, many immune network algorithm models only simulate the function of a certain part of the immune system from a single perspective, and have not yet described the natural mechanism well.
Moreover, many current immune network algorithms are based on random probability operations, lacking dynamic behavior analysis of artificial immune networks, resulting in poor data classification and clustering effects

Method used

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Embodiment

[0030] Example, refer to figure 1 , a multi-agent data mining method based on artificial immune network, which integrates three typical strategies in multi-agent technology into the evolution process of the immune network, and obtains a memory cell representing the characteristics of the original data through the evolution of the immune network Finally, use the generated memory cell set to classify and cluster the data to be analyzed, including the following steps:

[0031] 1. Take the data that needs to be mined as the original data, normalize the original data so that its features are between [0,1], and eliminate the influence of the range of feature values ​​on the distance measure.

[0032] X i = X i - Min i Max i - ...

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Abstract

The invention discloses a data mining method combined with a multi-agent technology and an artificial immunity network. The typical strategy of the multi-agent technology is integrated into the immunity network. Neighborhood clone selection is introduced to an algorithm, the operation process is executed from the local part to the whole, and a natural evolution model of the immunity network can be simulated more comprehensively. Meanwhile, the competition and collaboration operation between antibodies is increased in the network training process, and the dynamic analysis capacity of the network is improved. By the adoption of the algorithm, in the data mining process, data clustering accuracy can be improved, and data classification accuracy can be improved as well.

Description

technical field [0001] The invention relates to the field of data mining, in particular to a multi-agent data mining method based on an artificial immune network. Background technique [0002] With the advent of the era of big data, extracting or discovering useful relationships or patterns and knowledge from large amounts of data has become a research hotspot. This process is also called data mining. Among them, clustering and classification are the main tasks of data mining. Introducing the artificial immune system algorithm into the field of data mining is a research hotspot in recent years. At present, the algorithms used in the field of data mining for the artificial immune system are all improved and modified based on de Castro's classic immune network algorithm aiNet. The main technologies are clonal selection, mutation, and network suppression. However, the biological immune system is a complex dynamic adaptive system, and it is very difficult to completely simulat...

Claims

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Application Information

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IPC IPC(8): G06F17/30
CPCG16B50/00G06F16/2465
Inventor 林小煌骆炎民
Owner HUAQIAO UNIVERSITY
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