Forecasting the Short-Term Traffic Flow in the Intelligent Transportation System Based on an Inertia Nonhomogenous Discrete Gray Model

<table class="figure-group"><tr class="fig-image" id="a"><td><object data="https://static.hindawi.com/articles/complexity/volume-2017/3515272/figures/3515272.fig.003a.svgz" name="3515272.fig.003a" type="image/svg+xml"></object></td></tr><tr class="fig-caption"><td><b>(a) </b>The simulated and forecasted curves of the congested flow (smooth traffic) on August 28</td></tr><tr class="fig-image" id="b"><td><object data="https://static.hindawi.com/articles/complexity/volume-2017/3515272/figures/3515272.fig.003b.svgz" name="3515272.fig.003b" type="image/svg+xml"></object></td></tr><tr class="fig-caption"><td><b>(b) </b>The simulated and forecasted curves of the congested flow on August 28</td></tr></table>

Complexity

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Figure 3

Figure 3: Forecasting the Short-Term Traffic Flow in the Intelligent Transportation System Based on an Inertia Nonhomogenous Discrete Gray Model 