Air traffic prediction with fuzzy constraints

Abstract In view of the deficiencies of poor prediction accuracy, time-consuming and low efficiency of traditional traffic prediction models, fuzzy constraints are introduced into air traffic traffic system to represent some uncertain information in the field of artificial intelligence, and construct a fuzzy constraint-based air traffic flow prediction The fuzzy constraint-based air traffic prediction model is constructed. By analyzing the decision vector, fuzzy parameter vector and fuzzy constraint set, the prediction model is proposed. The air traffic flow prediction model is built by analyzing the decision vector, fuzzy parameter vector and fuzzy constraint set that affect the fuzzy constraint, and proposing the construction process of the prediction model. The experimental results show that the air traffic flow prediction model can be used to predict the air traffic flow. The experimental results show that the improved prediction model is better than the traditional prediction model in predicting air traffic flow. The results show that the improved prediction model has better prediction results, shorter time consumption and higher accuracy than the traditional prediction model.