| In general,when we deal with some special things,we often need to use tools to study the classification o f things,for example,the geological exploration of resources according to the geophysical indicators of sample classification;biological research in archaeological unearthed bones according to the shape and size of their classification;meteorological satellite systems for monitoring the data information is very complex and huge,they need to be classified according to different indicators of consolidation,then in-depth analysis,in order to make an accurate prediction,clustering analysis has emerged.Clustering analysis technology is a keeper of the specific or abstract object divided into different categories of science,which does not have a prior classification.It is also a ki nd of important human behavior.With the rapid development of computer and information technology,the data information presents the trend of rapid growth.As an important method of data mining,cluster analysis has been concerned by more and more people.K-Means algorithm is based on the division of the algorithm,because of its simple operation,easy to understand the characteristics of the principle,has been widely used and studied,and become one of the ten typical data mining algorithms.However,K-Means algorithm also has its own shortcomings,that is,k value is not good to determine the problem,the initial center can only be randomly selected,easy to fall into the local optimal solution,and so on,the algorithm is very unstable.Therefore,this paper introduces genetic algorithm based on K-Means clustering algorithm,which is a method to search the optimal solution by imitating the process of biological evolution,which has a good global search capability.According to the characteristics of the two algorithms,this paper proposes a hybrid algorithm of improved genetic algorithm in the application of K-Means clustering,and the simulation experiments with the sample data set,experiments show that this algorithm has good clustering effect in applicat ion.The work of this paper is divided into two parts: 1)The first part mainly introduces the basic concepts of cluster analysis,K-Means algorithm and genetic algorithm.The basic idea of K-Means algorithm and genetic algorithm is introduced in this paper,the composition and basic elements of the algorithm are described,and the application of the algorithm is also introduced.2)The second part mainly introduces an improved K-Means clustering algorithm based on genetic algorithm,and this algorithm in t he chromosome encoding,the selection of fitness function,selection,crossover and mutation operator,the design and improvement of K-Means algorithm and genetic algorithm combined with the operation and other aspects of the comprehensive description.Fin ally,in order to verify the effectiveness of the proposed algorithm is tested,based on the experimental results of the two methods of comparative analysis,confirmed the feasibility of this method and good clustering performance. |
