带有振荡因子灰色模型的短时交通流建模与预测
首发时间:2012-01-11
摘要:短时交通流预测应具备实时性、准确性和可靠性,其预测问题是交通控制与诱导中的一个难点,结果的好坏直接关系到交通控制与诱导的效果,因此,短时交通流预测是先进交通管理信息系统中关键技术问题之一。针对交通流数据的不确定性、周期振荡性等特点,本文提出带有振荡因子的灰色模型,利用离散傅里叶变换求解周期参数,并采用最小二乘法估计模型参数。利用实际数据通过与经典 灰色模型的预测精度比较分析,验证了该模型预测交通流的有效性和实用性。
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Modeling and Forecasting of Short-term Traffic Flow Based on Grey Model with Oscillation Factor
Abstract:Short-term traffic flow predictive should have the features of real-time, accuracy and reliability, the predictive problem is a difficulty trouble in traffic control and induction, the result of the forecast affects the effects of the traffic control and inducing directly. So the short-term traffic flow predictive is one of the key technical problems in advanced traffic management information system. The traffic flow data has the characteristics of uncertainty and oscillations periodicity, this paper presents a new grey model which have the oscillation factor, using discrete Fourier transform to solving the cycle parameters, and estimate the parameters of the model by using the least squares .At last, we use the real data to compare and analysis the prediction accuracy of this model with the classical Grey model, the result confirms that this model is verified by forecasting traffic flow validity and practicability.
Keywords: Level than;Development coefficient;Short-term traffic flow;Grey model.
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