Clustering Problem Based On Ant Colony Algorithm And It's Application In HRM

Along with fast development of network technology and database technology, the computer can save the large-scale data. On the other hand, the traditional data analysis tools such as the management information system can only proceed with surface of the data, and the deep data proceeding capability is not well. The conflict between the capability of the data supply and the capability of the data analysis is more and more prominent. So a kind of automatization technology is imminently needed to deeply proceed with the data. At this time, the technology of data mining has been put forward. As one of the most important domain of data mining, clustering analysis classifies the data into natural communities and give each community characteristic description. Clustering analysis is one of the basic methods of the data mining and knowledge finding and it is a non- surveillance data classification method. By using the advanced algorithm, we can find the useful information and improve the quality of data analysis and explain. This information can be the foundation of other data analysis tools for re-analyzing the data. Because of the above reasons, it's very significative for us to research how to improve the performance of the clustering analysis algorithm.There are many clustering analysis algorithms. The famous algorithms are these: K-means algorithm, K-center algorithm, C-means algorithm, FCM algorithm and so on. Ant Colony Algorithm is a new ecotypic optimization algorithm and its characteristics are positive feedback and distributed computing. It's indicated that ant...