The Research On Clustering Algorithm Based On Swarm Intelligence

With the acceleration of modernization,more and more data are produced in people's daily life.How to quickly gain potentially useful information resources from this huge amount of data,and guide people to make correct decisions,which is inseparable from data mining.Clustering,as an important branch of data mining,has unique advantages and is an important research topic for researchers.However,the clustering algorithm has some disadvantages,such as sensitive initial clustering center and poor global search ability,and it is of great significance to study how to further improve the shortcomings of the clustering algorithm to solve the problems encountered in social practice.Swarm Intelligence(SI)is a kind of artificial intelligence technology.As a hot topic of scientific research,it has been widely paid attention to by researchers and applied in many fields.This paper discusses the application of swarm intelligence optimization algorithm's unique optimization performance to solve the problems existing in the traditional clustering algorithm.Through the in-depth study of artificial bee colony algorithm,the performance of artificial bee colony optimization algorithm is improved,and combined with the traditional K-means clustering algorithm,the problems existing in the clustering method are improved.The main work of this paper are as follows:(1).The traditional artificial bee colony algorithm is improved.Firstly,chaos mapping and reverse learning method are used to initialize the bee colony,so as to increase the diversity of the population and enhance their ability to jump out of a local optimal solution;secondly,in the search process,the local optimal and global optimal location updating formula is used to improve the efficiency of the iterative optimization process.The effectiveness of the new algorithm is tested by simulation experiments.which speeds up the convergence of the algorithm to the global optimal solution,and has a certain stability.(2).Using swarm intelligence algorithm can effectively improve the clustering efficiency of clustering algorithm.The improved artificial bee colony algorithm proposed in this paper is combined with the traditional K-means algorithm for clustering,so that the efficiency and accuracy of clustering analysis are improved.The feasibility of the algorithm is proved by experiments,and the efficiency and performance of the new algorithm are greatly improved.