Design And Implementation Of Foreign Student Evaluation System Based On Fuzzy Clustering

The use of the international student management service platform has accumulated a large number of data on students.And the data itself implies a large number of valuable decision information.But the current service platform just simply records or backup the data without deep analysis and processing,thus making it impossible to provide auxiliary decision by using these data.Aiming at the current situation of the service platform of the international student management of China university of petroleum(east China),this thesis uses the data mining technology to do the data analysis and find out valuable information hidden in these large amounts of data.Due to the relationship between the data object may not be clear,so it chooses the fuzzy clustering methods for clustering analysis of students information,so that we can solve the problem of fuzziness between data objects,making the results of the clustering more reasonable and humanization.Based on the clustering analysis of the information in the platform,we can get the evaluation of the foreign students in China and achieve the further utilization of the information.Based on the analysis of the existing platform,it adopts the fuzzy clustering FCM algorithm construct the evaluation model of the foreign students in China.The model consists of six steps,including Factor set U determination,parameters determination,data preprocessing,fuzzy clustering analysis and the evaluation result mapping.Finally,based on the constructed evaluation model of Chinese students in China,it can make a relatively reasonable and correct evaluation and classification of each student.According to the results of the system analysis,it is possible to make better use of foreign students in education and management.While improving the efficiency of work,it can also promote the development of the foreign students in China.