The embodiment of the invention discloses a short-term traffic flow prediction method and system based on Bayesian optimization. The method comprises the steps of: collecting original traffic flow data passing through a fixed road position in a fixed time interval, carrying out preprocessing on the original traffic flow data according to a seasonal model algorithm to generate time sequence trafficflow data; constructing a short-term traffic flow prediction model based on a support vector regression machine, and training the short-term traffic flow prediction model; calculating a mean absolutepercentage error of the short-term traffic flow prediction model, and acquiring the prediction precision of the short-term traffic flow prediction model according to the mean absolute percentage error; optimizing the model parameters corresponding to the prediction precision according to a Bayesian optimization algorithm until a target short-term traffic flow prediction model is generated; and predicting the short-term traffic flow according to the target short-time traffic flow prediction model. According to the embodiment of the invention, the generalization ability of the short-term traffic flow prediction model is improved, the prediction precision is improved, and convenience is provided for intelligent traffic.
本发明实施例公开了一种基于贝叶斯优化的短时交通流预测方法及系统,方法包括:采集固定道路位置的固定时间间隔内通过的原始交通流量数据,根据季节模型算法对原始交通流量数据进行预处理,生成时序交通流数据;构建基于支持向量回归机的短时交通流预测模型并进行训练;计算短时交通流预测模型的平均绝对百分误差,根据平均绝对百分误差获取短时交通流预测模型的预测精度;根据贝叶斯优化算法对预测精度对应的模型参数进行优化,直至生成目标短时交通流预测模型;根据目标短时交通流预测模型对短时交通流量进行预测。本发明实施例提高了短时交通流量预测模型的泛化能力,提高了预测精度,为智能交通提供了便利。
Short-term traffic flow prediction method and system based on Bayesian optimization
一种基于贝叶斯优化的短时交通流预测方法及系统
2020-05-22
Patent
Electronic Resource
Chinese
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