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This paper focuses on traffic flow forecasting approach based on soft computing tools. The soft computing tools used is Particle Swarm Optimization (PSO) with Wavelet Network Model(WNM). The forecast of short-term traffic flow in timely and accurate is one of important contents of intelligent transportation system research. The modelling of traffic characteristics and the prediction of future traffic...
Accurate short-term traffic flow forecasting has become a crucial step in the overall goal of better road network management. A combination approach based on Principal Component Analysis (PCA) and Wavelet Neural Network(WNN) is presented for short-term traffic flow forecasting. The historical data of the forecasted traffic volume and interrelated volumes have been processed by PCA first, and then...
This paper uses the K-NN based nonparametric regression to forecast the short term traffic flow, applies the prediction interval calculated by K to forecast during unconventional road condition, and improves the forecasting results. Finally, nonparametric regression's advantages of high accuracy and strong transplant ability are showed while being compared with neural network.
Interval type-2 fuzzy logic system cascaded with neural network, interval type-2 fuzzy neural system (IT2FNS), is proposed to handle complicated uncertainties in short-term traffic flow forecasting. A secondary membership function is obtained through fuzzy reasoning. The strong consistent estimates of the unknown parameters of the neural network structure are developed. The secondary membership function...
The real time adaptive control of urban traffic, as a complex large system, usually needs to know the traffic of every intersection in advance. So traffic flow forecasting is a key problem in the real time adaptive control of urban traffic. A kind of typical truck multi- intersection section of city road is researched in this paper. A dynamic recursion network which is called Elman neutral network...
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