The Design And Implementation Of University Employment Management System Based On Ant Colony Algorithm

With the transition of higher education to mass education, the number of graduates increases dramatically, then the employment problem has become the focus of the society. A large number of graduates leave a mass of data, how to use which to provide the basis of scientific management for the university administrators has become a pressing problem. The development of computer technology makes it possible to solve the problem.Firstly, after researching the basic ideas, principles, processes, and application of the ant colony algorithm in the framework of the swarm intelligence, some well-known improved versions of the ant colony algorithm are researched deeply, which provides the basis and reference for the research of the paper's core theory and the practical system's application.Secondly, cluster analysis has been done to analyze system-cluster method and K-cluster method. The former one gets a more detailed study, and the K-prototypes algorithm is emphasized, including its origin, development, and basic algorithm ideas, which provides a brief introduction of the following application of the algorithm. Then the research focus is the cluster analysis of the university employment data based on the ant colony algorithm, and the preparing work as the preprocess and the purification of the university employment data. The data analysis module of the university employment management system is researched in two ways: improve the adaptive ant colony algorithm and analyze its principles and the procedures of its improved version; research the cluster analysis technology of the fusion ant colony algorithm and K-prototypes algorithm, and research and discuss the advancement of the ant cluster algorithm and the fusion of the ant algorithm and K-prototypes algorithm. After that, on the basis of the above algorithm, the core algorithm is programmed.Finally, the technology and related tools used in the system development and how to use the system environment are studied. The functions to achieve of this system analyze and implement the university employment management system from three structures, mainly design the realization methods of each functional module in the system, including the foreground realization, the background management, and the database operation. The experimental data and functions are tested, and the results show that the cycle numbers of the fusion ant colony algorithm and K-prototypes algorithm decrease apparently, which greatly overcomes the defects appearing when the common ant colony algorithm predetermines the number of clusters.