The invention relates to the technical field of intelligent traffic systems, and particularly provides a short-time traffic flow prediction method and system, and the method comprises the steps: obtaining a traffic flow sequence; decomposing and reconstructing the traffic flow sequence through an ensemble empirical mode decomposition method to obtain a plurality of traffic flow sequence components and residual components; calculating the correlation between the traffic flow sequence component and the traffic flow sequence according to a dynamic time warping algorithm to obtain a high correlation component and a low correlation component; performing calculation according to the high-correlation component and the low-correlation component to obtain normalized data; inputting the normalized data into an LSTM model to obtain a plurality of initial prediction results; and carrying out superposition summation on the plurality of initial prediction results to obtain a prediction result. The prediction accuracy is remarkably improved, the complex and changeable characteristics of the traffic flow can be flexibly handled, and a solid and reliable decision basis is provided for a traffic management department.
本申请涉及智能交通系统技术领域,具体提供了一种短时交通流预测方法及系统,所述方法包括:获取交通流序列;通过集合经验模态分解法对所述交通流序列进行分解重构,得到多个交通流序列分量和剩余分量;根据动态时间规整算法计算所述交通流序列分量和所述交通流序列的相关性,得到高相关分量和低相关分量;根据所述高相关分量和所述低相关分量进行计算得到归一化数据;将所述归一化数据输入至LSTM模型,得到多个初始预测结果;将多个所述初始预测结果进行叠加求和,得到预测结果。不仅显著提升了预测的准确性,而且能够灵活应对交通流量的复杂多变特性,为交通管理部门提供了坚实可靠的决策依据。
Short-term traffic flow prediction method and system
一种短时交通流预测方法及系统
2025-03-21
Patent
Electronic Resource
Chinese
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