Improving QGA-ELM Inversion Model of Rice Leaf Area Index Based on UAV Remote Sensing Image

<table class="figure-group"><tr class="fig-image" id="a"><td><object data="https://static.hindawi.com/articles/misy/volume-2022/9658966/figures/9658966.fig.009a.svgz" name="9658966.fig.009a" type="image/svg+xml"></object></td></tr><tr class="fig-caption"><td><b>(a) </b>Linear model</td></tr><tr class="fig-image" id="b"><td><object data="https://static.hindawi.com/articles/misy/volume-2022/9658966/figures/9658966.fig.009b.svgz" name="9658966.fig.009b" type="image/svg+xml"></object></td></tr><tr class="fig-caption"><td><b>(b) </b>LS-SVR model</td></tr></table>

<div>Measured value versus predicted value of the linear and LS-SVR models in prediction set of LAI.</div>

Mobile Information Systems

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Figure 9

Figure 9: Improving QGA-ELM Inversion Model of Rice Leaf Area Index Based on UAV Remote Sensing Image 