Summary of the described ionospheric parameters forecasting based on NN.
|Prediction lead time
|Sai Gowtam & Tulasi Ram (2017)
|ANN prediction model of NmF2 and hmF2 as function of LT, LAT, LONG, SEASON
|NmF2 and hmF2 percentage error ranged between 15% and 20%. The NmF2 model performance decreases at low latitudes during the predawn hours and around midnight at middle-high latitude.
|The hmF2 model performance decreases at low latitude at postsunset.
|Tulunay et al. (2006)
|Regional TEC forecasting model, NN
|10 min up to 1 h
|Short term forecasting. RMSE increases with forecasting horizon up to about 4 TECU over mid latitude grid points.
|Habarulema et al. (2011)
|ANN regional TEC variability forecasting model as function of time of the day, season, solar and magnetic activity, latitude and longitude
|The model accuracy is decreases under geomagnetically disturbed conditions.
|Huang & Yuan (2014)
|TEC single station forecasting model based on BP NN and RBF NN
|Short term forecasting. RMSE less than 5 TECU, the model performance decreases at lower latitude.
|Cherrier et al. (2017)
|Global TEC maps forecasting model based on recurrent NN and TEC global map by CODE
|RMSE increases with forecasting horizon. The model performance decreases under disturbed conditions.
|Global TEC maps forecasting model NN combined with GIM map
|24-h or more
|Equatorial Ionospheric Anomaly not represented
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