Research On Prediction And Analysis Of Score Based On BP Neural Network And Apriori Algorithm

With the rapid development of network technology and database technology,the construction of digital campus has been gradually popularized,and the teaching management system is maturing day by day,which has been paid attention to by the education department.At present,the teaching management system stores a lot of teaching data,traditional statistical analysis method can not analyze the laws behind data.Users can use data mining technology,not only can access,query,modify and other operations of the current data,but also can use related data mining algorithm mining and analyzing massive data in database to find hidden,unknown and meaningful information behind data.But at present,in university education,it is often unsatisfactory,and people do not do deep mining research on data resources and campus card data resources in the database,and does not make full use of data resources.Educational data mining has always been the focus of educational researchers,prediction of student score has always been an important research direction in the field of educational data mining.Traditional prediction methods fail to achieve the expected goal.BP Neural network prediction makes up for the shortcomings of traditional prediction.In addition,traditional prediction methods often fail to consider students' daily behavior information.Data in campus cards are accumulated by students' learning and life.Data often contain important information.This paper not only starts from students' historical score data,but also studies students' behavior information to predict students' score accurately and provide early warning for students and Use Apriori algorithm to discusses the relationship between students' breakfast,library lending and student achievement,and explores the relationship between courses,and explores the relationship between courses,gives pertinent suggestions to the arrangement of school teaching.