Trinity enrollment and admission probability prediction method based on neural network

The invention discloses a trinity enrollment and admission probability prediction method based on a neural network. The method comprises the following steps that: 1) association analysis; 2) obtaininga neural network prediction model; 3) training and evaluating the prediction model; and 4) obtaining an enrollment probability. The step of association analysis that three lessons are selected from six subjects to take an examine and an examinee selects the six lessons comprises the following steps that: 1.1) collecting and preparing data; 1.2) carrying out problem description; 1.3) using an Apriori algorithm to simplify calculation; 1.4) using the Apriori algorithm to find a frequent set; and 1.5) mining an association rule. The step 4) comprises the following steps that: according to general examination achievements, elective achievements and reexamination achievements obtained by neural network prediction, obtaining the comprehensive achievement of the examinee by the scoring standardof a college, ranking the