Effective Estimation of Hourly Global Solar Radiation Using Machine Learning Algorithms

<table class="figure-group"><tr class="fig-image" id="a"><td><object data="https://static-preview.hindawi.com/articles/ijp/volume-2020/8843620/figures/8843620.fig.008a.svgz" name="8843620.fig.008a" type="image/svg+xml"></object></td></tr><tr class="fig-caption"><td><b>(a) </b>Best Validation Performance is 0.002638 at epoch 359</td></tr><tr class="fig-image" id="b"><td><object data="https://static-preview.hindawi.com/articles/ijp/volume-2020/8843620/figures/8843620.fig.008b.svgz" name="8843620.fig.008b" type="image/svg+xml"></object></td></tr><tr class="fig-caption"><td><b>(b) </b>Best Validation Performance is 0.0026333 at epoch 50</td></tr></table>

<div>The MFFNN performance plots of best models: (a) Isparta and (b) Kahramanmaras.</div>

International Journal of Photoenergy

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Figure 8

Figure 8: Effective Estimation of Hourly Global Solar Radiation Using Machine Learning Algorithms 