Ensemble learning activity scheduler for activity based travel demand models

Keyphrases

• Activity-based Travel Demand Model 100%
• Learning Activities 100%
• Travellers 100%
• Ensemble Learning 100%
• Scheduler 100%
• Time Duration 40%
• Activity Duration 40%
• Activity-dependent 20%
• Daily Activities 20%
• Time Use 20%
• Activity Patterns 20%
• Sociodemographic Characteristics 20%
• Random Forest 20%
• Population-based Cohort 20%
• Machine Learning Techniques 20%
• Nova Scotia 20%
• Halifax 20%
• Response Variable 20%
• Modeling Framework 20%
• Activity Study 20%
• Activity-based Model 20%
• Activity Scheduling 20%
• Temporal Features 20%
• Activity Location 20%
• Homogeneous Population 20%
• Activity Data 20%
• Activity Type 20%
• Travel Behavior 20%
• Daily Rhythm 20%
• Space-time Activity 20%
• Research Survey 20%
• Random Forest Regression 20%
• Efficient Machine Learning 20%
• Homogeneous Time 20%
• Attribute Recognition 20%
• Skeleton Schedule 20%
• Rule-based Algorithm 20%
• Time-diary Data 20%
• Representative Pattern 20%
• Temporal Attributes 20%
• Decision Heuristics 20%
• Active Travel 20%
• New Modeling 20%

Computer Science

• Random Decision Forest 100%
• Temporal Information 100%
• Activity Duration 100%
• Learning Experiences 100%
• Ensemble Learning 100%
• Daily Activity 100%
• Machine Learning Technique 50%
• Modeling Framework 50%
• Individual Model 50%
• Representative Pattern 50%
• Response Variable 50%
• Temporal Feature 50%
• Demographic Characteristic 50%
• Varying Structure 50%