The forecasting and modeling of ionospheric
scintillation effects are crucial for precise satellite posi-
tioning and navigation applications. In this paper, a Neural
Network model, trained using Particle Swarm Optimization
(PSO) algorithm, has been implemented for the prediction of
amplitude scintillation index (S4) observations. The Global
Positioning System (GPS) and Ionosonde data available at
Darwin, Australia (12.4634° S, 130.8456° E) during 2013
has been considered. The correlation analysis between GPS
S4 and Ionosonde drift velocities (hmf2 and fof2) data has
been conducted for forecasting the S4 values. The results
indicate that forecasted S4 values closely follow the mea-
sured S4 values for both the quiet and disturbed conditions.
The outcome of this work will be useful for understanding
the ionospheric scintillation phenomena over low latitude
regions.

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• Ionospheric scintillation forecasting model based on NN-PSO technique