Firework algorithm-based clustering method and device

Abstract

The invention provides a firework algorithm-based clustering method and device, and the method comprises the steps: carrying out the initialization processing of a to-be-clustered sample point set, obtaining a first-generation firework group comprising a preset number of fireworks, and obtaining a next-generation firework group according to the Gaussian mutation operator and cost function of eachsample point and the fitness of each firework, judging whether the next-generation firework group meets a preset termination condition or not, if yes, determining K clustering centers included in fireworks with the highest fitness in the next-generation firework group as target clustering centers, and obtaining a clustering result according to the distance between each sample point in the to-be-clustered sample point set and each target clustering center. According to the embodiment of the invention, the next-generation firework group is obtained based on the fitness and the Gaussian mutationoperator, so that the clustering center can be obtained globally, the problem that clustering falls into local optimum is avoided, and the clustering accuracy is improved.

Description

technical field [0001] Embodiments of the present invention relate to computer technology, and in particular to a clustering method and device based on a fireworks algorithm. Background technique [0002] In natural science and social science, there are a large number of classification problems, in which the process of dividing a collection of physical or abstract objects into multiple classes composed of similar objects is called clustering, and a clustering set usually includes a Cluster centers and multiple sample points. [0003] At present, the traditional clustering method usually randomly selects sample points from the data set as the initial cluster center, calculates the distance between each sample point in the data set and the initial cluster center, and divides each sample point into the nearest cluster center. In the clustering set to which the class center belongs, secondly, for each clustering set, determine the positions corresponding to the centroids of all...

AI Technical Summary

Problems solved by technology

[0005] The embodiment of the present invention provides a clustering method and device based on the fireworks algorithm to overcome the fact that the clustering result is prone to fall into local optimum

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