A New Hybrid Model FPA-SVM Considering Cointegration for Particular Matter Concentration Forecasting: A Case Study of Kunming and Yuxi, China

<table class="figure-group"><tr class="fig-image" id="a"><td><object data="https://static.hindawi.com/articles/cin/volume-2017/2843651/figures/2843651.fig.004a.svgz" name="2843651.fig.004a" type="image/svg+xml"></object></td></tr><tr class="fig-caption"><td><b>(a) </b>Kunming</td></tr><tr class="fig-image" id="b"><td><object data="https://static.hindawi.com/articles/cin/volume-2017/2843651/figures/2843651.fig.004b.svgz" name="2843651.fig.004b" type="image/svg+xml"></object></td></tr><tr class="fig-caption"><td><b>(b) </b>Yuxi</td></tr></table>

<div>The original PM<sub>2.5</sub> and PM<sub>10</sub> of Kunming and Yuxi.</div>

Computational Intelligence and Neuroscience

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Figure 4

Figure 4: A New Hybrid Model FPA-SVM Considering Cointegration for Particular Matter Concentration Forecasting: A Case Study of Kunming and Yuxi, China 

Figure 4 | A New Hybrid Model FPA-SVM Considering Cointegration for Particular Matter Concentration Forecasting: A Case Study of Kunming and Yuxi, China 