@Article{EAJAM-12-2,
author = {Shen, Qin-Qin and Yang, Cao and Zeng, Bo and Shi, Quan},
title = {Stable Computation of Least Squares Problems of the OGM(1,N) Model and Short-Term Traffic Flow Prediction},
journal = {East Asian Journal on Applied Mathematics},
year = {2022},
volume = {12},
number = {2},
pages = {264--284},
abstract = {<p style="text-align: justify;">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.</p>},
issn = {2079-7370},
doi = {https://doi.org/10.4208/eajam.280921.141121},
url = {https://global-sci.com/article/82466/stable-computation-of-least-squares-problems-of-the-ogm1n-model-and-short-term-traffic-flow-prediction}
}