鉴于传统流量预测模型存在预测精度差、耗时长、效率低的不足，将模糊约束引入空中交 通系统，用于表示人工智能领域中一些不确定的信息，构建了基于模糊约束的空中交通流量预测模型。通过分析影响模糊约束的决策向量、模糊参数向量及模糊约束集三个因素，提出预测模型 的构建流程，选取空中交通路线多转折点，并获取模糊矩阵，建立了空中交通流量预测模型。实验结果表明，对空中交通流量进行预测时，采用改进的预测模型相比传统预测模型的预测结果较 优、耗时较短、精度较高。

In view of the shortcomings of the traditional flow prediction model, such as poor prediction accuracy, long time consumption and low efficiency, fuzzy constraint was applied to describe some uncertain information of artificial intelligence in air traffic system, and an air traffic flow forecasting model was built based on the fuzzy constraint. By analyzing three factors of decision vector, fuzzy parameter vector and fuzzy constraint set, the construction process of prediction model was put forward, some multiple turning points of air traffic route was chosen, the fuzzy matrix was obtained, and the air traffic flow forecasting model was built. The experimental results show that the improved prediction model has bet⁃ ter prediction effect, shorter time consumption and higher accuracy compared with the traditional predic⁃ tion model, when forecasting the air traffic flow.