## 4 Results and Discussion
On 31 March 2017, the percentage of ionospheric scintillation reached 43%, which is ten percent less than the same day in 2015. The percentage of ionospheric scintillation and S4 on 31 July and 31 January 2017 also decreased compared to the same day in 2015. By the reduction in solar activity in 2020, the percentage of ionospheric scintillation and S4 values decline during these three years. In 2020, the percentage of ionospheric scintillation during these three days reached a quarter of that on the same day in 2017, meaning that on 31 March, the percentage of ionospheric scintillation occurrence decreased to 10%. The lowest average S4 is 0.12, and the lowest percentage of ionospheric scintillation is 7% on 31 July 2020. RMSE and R-square values in Table 2 show that the 24-h forecast accuracy for 2020 was higher than that in 2017 and 2015. This can be seen by the trend for the 30-day modeling accuracy during these three years. On 31 July 2020, the highest R-square and the lowest RMSE values are obtained among these nine observation days in 2015, 2017, and 2020. On 31 January and then on 31 March of the same year, the highest accuracy is recorded after 31 July 2020. In 2015, the prediction's accuracy decreases compared to 2020, and this descending trend is repeated for 2015. The prediction accuracy on 31 March 2015 is the lowest prediction accuracy among these three years with a value of 0.80 for R-square and 0.022 for RMSE. Figure 3 demonstrates these values in which the observed and predicted values of S4 are presented for the three 24-h intervals. \begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline  & \multicolumn{3}{c}{**2015**} & \multicolumn{3}{c}{**2017**} & \multicolumn{3}{c}{**2020**} \\ \hline
**Period of Time** & **1–30** & **1–30** & **1–30** & **1–30** & **1–30** & **1–30** & **1–30** & **1–30** & **1–30** & **1–30** & **1–30** \\  & **January** & **March** & **July** & **January** & **March** & **July** & **January** & **March** & **July** \\ \hline Mean S4 & 0.22 & 0.24 & 0.20 & 0.19 & 0.21 & 0.17 & 0.15 & 0.16 & 0.14 \\ \hline Max S4 & 0.42 & 0.51 & 0.38 & 0.44 & 0.49 & 0.41 & 0.41 & 0.43 & 0.36 \\ \hline RMSE & 0.009 & 0.008 & 0.009 & 0.008 & 0.007 & 0.008 & 0.007 & 0.006 & 0.007 \\ \hline R-Squared & 0.92 & 0.91 & 0.92 & 0.92 & 0.92 & 0.93 & 0.93 & 0.92 & 0.94 \\ \hline Scintillation Occurrence (S4 \(>\) 0.2) & 56\% & 61\% & 53\% & 45\% & 51\% & 41\% & 25\% & 28\% & 21\% \\ \hline \hline \end{tabular}
\end{table} 
Table 1: The difference between observed and GANN-modeled S4 during the 30 days for January, March, and June in 2015, 2017, and 2020. In the next step, we consider ROTI values to identify and better predict the ionospheric scintillation phenomenon. The ROTI values are considered in the same period as the previous study of the S4, i.e., the three months of January, March, and June in 2015, 2017, and 2020. The highest mean ROTI observed in March 2015 is equal to 1.14, followed by January (0.97) and July (0.96). The average observational values of the ROTI in 2017 decrease compared to 2015, and this descending trend continues in 2020. In 2017, the average observational ROTI occurred in March, January, and July, in that order. The lowest average observational ROTI value among these three years observed in July 2020 is equal to 0.74. The ROTI modeling accuracy increases when geomagnetic activity decreases over 30-day intervals. Similar to the first step, parameters such as RMSE, R-square, and residuals were considered by GANN for modeling the ROTI. Table 3 presents the data from the modeling conducted in the present study. According to the R-square and RMSE values, it can be seen that the accuracy of modeling for the 30-day interval in 2020 is better compared to the 30 days in 2015 and 2017. Therefore, 2020 is the most accurate in