Explore data classification algorithm based on SVM and PSO for education decision

Sino-foreign cooperative education plays an important role in modern Chinese education system and more and more students join the projects every year. However, some of the students can not do well in such cooperative projects teaching in a western style and in another language. Therefore, what kind of students is appropriate for Sino-foreign cooperative project? This paper proposes Sino-foreign cooperative education selection analysis using support vector machine (SVM) and PSO algorithm. Support Vector Machine is firstly applied in studying on the topic and it is used to precisely classify the students into who are suitable for Sino-foreign projects and who are not. This method can help universities to figure out what features the students should have in the cooperative projects and has a far-ranging application in management. Experimental result shows that the proposed algorithm is effective.