A Novel Parallel Series Data-driven Model for IATA-coded Flight Delays Prediction and Features Analysis

Keyphrases

• Feature Analysis 100%
• Data-driven Model 100%
• Time Series Data 100%
• Prediction Analysis 100%
• International Air Transport Association 100%
• Flight Delay 100%
• Parallel-series 100%
• Flight Delay Prediction 100%
• Time Series Model 57%
• Bidirectional Extreme Learning Machine 57%
• Sampling Approach 28%
• Hong Kong 14%
• Airlines 14%
• Generalization Performance 14%
• Noisy Data 14%
• Data-driven Approach 14%
• Historical Data 14%
• Learning Rate 14%
• Decision Boundary 14%
• Multi-class 14%
• Covariance 14%
• Airport 14%
• Hidden Patterns 14%
• Gradient Descent 14%
• Network Generalization 14%
• Imbalanced Data 14%
• Air Traffic Control 14%
• Multi-label Classification 14%
• Air Traffic Management 14%
• International Airlines 14%
• Gradient Ascent 14%
• Contingency Measures 14%
• Alternate Strategy 14%

Engineering

• Air Transport 100%
• Data Series 100%
• Extreme Learning Machine 66%
• Airlines 33%
• Application Area 16%
• Decision Boundary 16%
• Noisy Data 16%
• Air Traffic 16%
• Historical Data 16%
• Objective Function 16%
• Traffic Management 16%
• Traffic Control 16%
• Gradient Descent 16%

Computer Science

• Extreme Learning Machine 100%
• Sampling Approach 50%
• Historical Data 25%
• Driven Approach 25%
• Gradient Descent 25%
• Generalization Performance 25%
• Case Study 25%
• Objective Function 25%
• Traffic Management 25%
• Traffic Control 25%
• Decision Boundary 25%
• Application Area 25%
• Learning Rate 25%