In Business Intelligence System the traditional cluster analysis has been widely used, but there are still some problems. When dealing with large data convergence, for example, it will sometime slower and more prone to local minimum problems. In view of these problems, the paper presents a cluster analysis method based on the improved genetic algorithms, an application-oriented small and medium-sized enterprises and business intelligence system for HBI. The design and implementation of online analytical processing subsystems, and experiments show that the clustering algorithm is better quality and performance.The major work in this paper lists as follows:First, the papers detail-oriented business intelligence systems and related technology Cluster analysis of the existing technologies.Second, in response to the slow convergence, and cluster analysis of existing early, a cluster analysis based on the improved genetic algorithms, including chromosome coding meet the terms crossover and mutation. Meanwhile the performance of this algorithm are compared with other cluster analysis algorithm, the experimental results show that the clustering algorithm is better quality and performance.Finally, described the business-oriented small and medium-sized enterprises in the online analytical processing subsystem HBI Intelligent... |