Enhancing COVID-19 Ensemble Forecasting Model Performance Using Auxiliary Data Sources

Keyphrases

• Ensemble Forecast 100%
• COVID-19 100%
• Model Performance 100%
• Ensemble Model 100%
• Auxiliary Data 100%
• Ensemble Methods 66%
• Challenging Problems 33%
• Trend Change 33%
• Adaptation 33%
• Rapid Growth 33%
• Proposed Methodology 33%
• Robust Performance 33%
• Real-time Forecasting 33%
• Deep Learning Model 33%
• Training Data 33%
• Growth Phase 33%
• Wave Phase 33%
• Multiple Datasets 33%
• Forecasting Model 33%
• Compartmental Model 33%
• Non-stationarity 33%
• Phase Information 33%
• Prediction Algorithms 33%
• Training Examples 33%
• Performance Properties 33%
• Transfer Entropy 33%
• Weighting Scheme 33%
• Entropy Method 33%
• COVID-19 Severity 33%
• Epidemic Dynamics 33%
• Non-stationary Time Series 33%
• Phase Prediction 33%
• Bayesian Model Averaging 33%
• Relevant Indicator 33%

Computer Science

• Deep Learning 100%
• Performance Model 100%
• Bayesian Model 100%
• Data Source 100%
• Training Data 100%
• Phase Information 100%
• Individual Model 100%
• Prediction Phase 100%
• Ensemble Technique 100%
• Training Example 100%