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- W2386041925 abstract "Accurately and efficiently predicting the short-term traffic flow is the premise of and key to the successful traffic management and control.However,due to the following characteristics of the short-term traffic flows including complexity,randomness,nonlinearity and uncertainty,prediction of short-term traffic is challenging,with low accuracy and poor real-time performance.Based on this observation,this paper combines the techniques of the projection pursuit regression and BP neural network to establish a combined model,which takes the advantages of both techniques.The solution algorithm of the model is provided.After applying the combined model for real-time short-term traffic,the model is found out to has a better real-time prediction capability." @default.
- W2386041925 created "2016-06-24" @default.
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- W2386041925 date "2012-01-01" @default.
- W2386041925 modified "2023-09-30" @default.
- W2386041925 title "Short-term Traffic Prediction Based on a Combined Projection Pursuit Regression and BP Neural Network Model" @default.
- W2386041925 hasPublicationYear "2012" @default.
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