Type Prediction of Student’s Achievement based on Grey Neural Network Optimized by GA

Students’ learning performance is predicted based on their online learning data, which is of great significance to evaluate the learning effect of school education and the reform and development of online education. In this paper, the characteristics of learning behaviour that constitute the influencing factors of students’ achievement are analysed and screened, and then a prediction model based on neural network and intelligent optimization algorithm is proposed. In this paper, the working principle of grey neural network (GNN) is described, the genetic algorithm (GA) is used to optimize the parameters, and the performance of the model is tested by simulation experiment. The experimental results show that, compared with the reference model, the prediction model optimized by GA parameters shows good prediction performance, and the prediction accuracy remains at a high level.