Prediction Model of Students' Learning Motivation Based on Combinatorial Optimization Algorithm

The strength of college students' learning enthusiasm directly affects their effect. Studying and predicting has positive significance for improving students themselves education. Existing methods have not involved how to select extract features related enthusiasm, so it is difficult meet the needs prediction. Therefore, this article takes English as an example conduct a research on prediction model based combinatorial optimization algorithm. Taking example, expounds in detail main manifestations predicts intention participate behaviors enumerated behaviors, judge gives construction method model. This study constructs network evaluation autonomy, finally outputs grade results autonomy evaluation. Based obtained predictions participation behavior intentions combined established through weighting inverted error predict regression enthusiasm. Experimental verify effectiveness constructed single