The invention provides a traffic flow data processing method and system based on a chaotic time sequence and chaos optimization. The method comprises the following steps: S1, constructing a chaotic time sequence by using a Lorenz system; s2, taking the chaotic time sequence as input data of an ACLSTM algorithm, and training the input data to obtain an ACLSTM model; s3, performing chaos optimization on the ACLSTM model by using a chaos optimization algorithm of Logistic mapping to obtain a trained ACLSTM model; and S4, processing the traffic flow data by using the trained ACLSTM model to obtain traffic flow data information. According to the method, the chaotic time sequence is constructed by using the Lorenz system, so that the ACLSTM model can capture the nonlinear trend of the data, the influence of an abnormal value on prediction is reduced, and the prediction performance of the ACLSTM model is improved.
本发明提出了一种基于混沌时间序列和混沌优化交通流数据处理方法及系统,方法包括以下步骤:S1、使用Lorenz系统构建混沌时间序列;S2、将所述混沌时间序列作为ACLSTM算法的输入数据,并对输入数据进行训练得到ACLSTM模型;S3、使用Logistic映射的混沌优化算法对ACLSTM模型进行混沌优化,得到训练好的ACLSTM模型;S4、使用训练好的ACLSTM模型对交通流量数据进行处理,得到交通流量数据信息。本申请通过使用Lorenz系统构建混沌时间序列,使ACLSTM模型能够捕捉到数据的非线性趋势,降低异常值对预测的影响,提高ACLSTM模型的预测性能。
Traffic flow data processing method and system based on chaotic time sequence and chaotic optimization
基于混沌时间序列和混沌优化交通流数据处理方法及系统
2024-02-23
Patent
Elektronische Ressource
Chinesisch
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