## 5 Results and Discussion
### Comparative and Qualitative Analysis
This model is useful for broader analyses but falls short in detailed, localized forecasting. The ConvGRU-L\({}_{\text{S}}\) prediction shows substantial deviation, underestimating both the intensity and spatial extent of scintillation, particularly failing to capture the northern expansion, resulting in a muted and less vibrant representation. The sunset map reveals significant ionospheric activity along the equatorial region, with a distinct scintillation hotspot near 10\({}^{\circ}\)S longitude. The scintillation is highly concentrated near the equator but with an increased area and intensity compared to sunrise. This period is known for heightened scintillation due to dynamic conditions at sunset, which enhance electron density fluctuations. This reflects the typical increase in ionospheric irregularities post-sunset, influenced by rapid changes in ionospheric plasma as it transitions from daylight to night conditions. The ConvGRU-L\({}_{\text{C}}\) prediction is remarkably accurate, mirroring the observed conditions in terms of both intensity and location. Although it slightly overestimates less intense scintillation areas, it remains effective at simulating sunset ionospheric dynamics. The ConvGRU-L\({}_{\text{log-cosh}}\) output extends the influence zone beyond the observed areas, generalizing ionospheric activity and diluting peak intensities, resulting in a less localized and precise depiction. The ConvGRU-L\({}_{\text{S}}\) model, with significant underestimations and poor localization of activity, shows the largest deviation from the observed conditions, indicating its limited utility in operational applications during significant ionospheric disturbances. Overall, the ConvGRU-L\({}_{\text{C}}\) model stands out for its fidelity in reproducing observed ionospheric conditions, while the other models exhibit varying degrees of effectiveness. The most intense ionospheric activity consistently occurs at sunset, possibly due to the compounded effects of solar heating throughout the day and the abrupt shift to night conditions. The variability between 2015 and 2020 highlights the impact of the solar cycle on ionospheric conditions, with 2015 showing more intense and widespread disturbances compared to 2020. The 2020 sunrise map, for instance, displays a less intense and more diffuse scintillation pattern, indicating a subdued response due to the solar minimum. The observed S4 map on July 31, 2020, at sunrise, shows ionospheric irregularities around the equatorial anomaly, with high scintillation levels concentrated in the EIA region. This increased activity correlates with the morning rise in solar radiation, which amplified ionospheric disturbances. The ConvGRU-L\({}_{\text{C}}\) model adeptly approximates the observed data, replicating the intensity and spatial distribution of scintillation zones, though it slightly overestimates the impact area. In contrast, the ConvGRU-L\({}_{\text{log-cosh}}\) model offers a broader depiction, diluting peak intensities and enlarging the affected area, which may compromise precision. The ConvGRU-L\({}_{\text{S}}\) model notably underestimates the intensity and breadth of disturbances, focusing on a narrower region and displaying markedly lower scintillation intensity, suggesting limited sensitivity to dynamic changes at sunrise. Atnoon, the scintillation pattern is milder with less spatial extent. The core areas of activity are less intense and more contained, reflecting reduced solar influences characteristic of a solar minimum. The ConvGRU-L\({}_{\text{C}}\) model precisely mirrors the observed high-intensity zones, though it modestly extends the disturbance area to the south, demonstrating a high capacity for detailed simulation of ionospheric dynamics suitable for precise forecasting. However, the ConvGRU-L\({}_{\text{log-cosh}}\) model generalizes ionospheric activity, extending intensity over a wider area and smoothing out peaks, which might limit its utility for precise forecasting.