The invention discloses a low-altitude traffic flow prediction method and system based on artificial intelligence. The method comprises the following steps: acquiring a complete traffic flow data set; obtaining traffic flow weight coefficients corresponding to various low-altitude aircrafts based on the complete traffic flow data set; obtaining a weather influence weight coefficient based on the complete traffic flow data set and the corresponding weather factor data set; obtaining a holiday activity traffic flow data set based on the complete traffic flow data set, and further calculating to obtain a holiday influence weight coefficient; acquiring multi-factor historical data of the target area, and correcting the multiple weight coefficients by calculating the variance of the historical data corresponding to each factor; constructing a traffic flow prediction sub-model corresponding to each factor according to the corrected weight coefficient, and training the traffic flow prediction sub-model; and obtaining a low-altitude traffic flow predicted value based on the trained model. According to the low-altitude traffic flow prediction method, more accurate low-altitude traffic flow prediction is realized by comprehensively considering various factors such as aircraft types, weather conditions, holiday and festival activities and the like.
本发明公开了一种基于人工智能的低空交通流量预测方法与系统,包括:获取完整交通流量数据集;基于完整交通流量数据集获得各类低空飞行器对应的交通流量权重系数;基于完整交通流量数据集和对应的天气因素数据集获得天气影响权重系数;基于完整交通流量数据集获得假日活动交通流量数据集,并进一步计算得到假日影响权重系数;获取目标区域多因素历史数据,通过计算每个因素对应历史数据的方差对以上多种权重系数进行校正;根据校正后的权重系数构建每个因素对应的交通流量预测子模型并进行训练;基于训练后的模型获得低空交通流量预测值。本发明通过综合考虑飞行器类别、天气条件、节假日活动等多种因素,实现了更精准的低空交通流量预测。
Low-altitude traffic flow prediction method and system based on artificial intelligence
一种基于人工智能的低空交通流量预测方法与系统
2025-05-30
Patent
Electronic Resource
Chinese
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