Performance analysis of FFNN and Kriging model on prediction of ionospheric TEC during April 2022–X 1.1 solar flare

INIS

• prediction 100%
• performance 100%
• neural networks 100%
• electrons 100%
• kriging 100%
• solar flares 100%
• data 85%
• errors 42%
• roots 14%
• correlations 14%
• tools 14%
• size 14%
• values 14%
• comparative evaluations 14%
• artificial intelligence 14%
• symmetry 14%
• data analysis 14%
• nasa 14%

Engineering

• Performance Analysis 100%
• Feedforward 100%
• Kriging Model 100%
• Network Model 100%
• Surrogate Model 80%
• Content Data 60%
• Data Server 40%
• Root Mean Square Error 20%
• Model Prediction 20%
• NASA 20%
• Artificial Intelligence 20%
• Mean Absolute Error 20%

Mathematics

• Neural Network 100%
• Kriging 100%
• Network Model 40%
• correlation coefficient ρ 20%
• Mean Square Error 20%
• Absolute Error 20%
• Statistical Parameter 20%
• Training Dataset 20%
• Scatter Plot 20%
• Residuals 20%
• Linear Regression 20%
• Symmetric Mean 20%