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A forecasting model of time series based on wavelet neural network

机译:基于小波神经网络的时间序列预测模型

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In accordance with the forecasting problem of the short-term traffic flow, a prediction model based on wavelet neural network was put forward. And then, by analyzing the influencing factors about short-term traffic flow, the forecasting method of short-term time series is constructed. Compared with other methods, the model can effectively improve the forecasting accuracy. The experimental results show that the model is very effective for the prediction of the short-term traffic flow.
机译:根据短期交通流量的预测问题,提出了一种基于小波神经网络的预测模型。 然后,通过分析关于短期交通流量的影响因素,构建了短期时间序列的预测方法。 与其他方法相比,该模型可以有效地提高预测精度。 实验结果表明,该模型对于预测短期交通流量非常有效。

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