Volume 1, Issue 1 (IJAE 2011)                   ASE 2011, 1(1): 21-28 | Back to browse issues page

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Fotouhi A, Montazeri M, Jannatipour M. Vehicle's velocity time series prediction using neural network. ASE 2011; 1 (1) :21-28
URL: http://www.iust.ac.ir/ijae/article-1-8-en.html
Vehicle's velocity time series prediction using neural network
A. Fotouhi , M. Montazeri , M. Jannatipour
Abstract:   (25805 Views)
This paper presents the prediction of vehicle's velocity time series using neural networks. For this purpose, driving data is firstly collected in real world traffic conditions in the city of Tehran using advance vehicle location devices installed on private cars. A multi-layer perceptron network is then designed for driving time series forecasting. In addition, the results of this study are compared with the auto regressive (AR) method. The least root mean square error (RMSE) and median absolute percentage error (MDAPE) are utilized as two criteria for evaluation of predictions accuracy. The results demonstrate the effectiveness of the proposed approach for prediction of driving data time series.
Keywords: vehicle, velocity, time series, prediction, neural networks
Full-Text [PDF 391 kb]   (7576 Downloads)    
Type of Study: Research | Subject: Vibration, noise, Acoustic
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