Stable Computation of Least Squares Problems of the OGM(1,N) Model and Short-Term Traffic Flow Prediction
Year: 2022
Author: Qin-Qin Shen, Yang Cao, Bo Zeng, Quan Shi
East Asian Journal on Applied Mathematics, Vol. 12 (2022), Iss. 2 : pp. 264–284
Abstract
The optimized grey multi-variable model, used to overcome the defects of the grey multi-variable model, is studied. Although this model represents a substantial improvement of the grey multi-variable one, unstable computation of the grey coefficients arising in ill-posed problems, may essentially diminish the model accuracy. Therefore, in the case of ill-posedness we employ regularization methods and use the generalized cross validation method to determine the regularization parameters. The methods developed are applied to the urban road short-term traffic flow prediction problem. Numerical simulations show that the methods proposed are highly accurate and outperform the grey multi-variate, the autoregressive integrated moving average, and the back propagation neural network models.
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Journal Article Details
Publisher Name: Global Science Press
Language: English
DOI: https://doi.org/10.4208/eajam.280921.141121
East Asian Journal on Applied Mathematics, Vol. 12 (2022), Iss. 2 : pp. 264–284
Published online: 2022-01
AMS Subject Headings:
Copyright: COPYRIGHT: © Global Science Press
Pages: 21
Keywords: Grey multi-variable model least squares problem ill-posed problem regularization technique traffic flow prediction.