Air passenger forecasting using Neural Granger causal Google trend queries

• Main Authors: Long, Chan Li, Guleria, Yash, Alam, Sameer
• Other Authors: Air Traffic Management Research Institute
• Format: Article
• Language: English
• Published: 2022
• Subjects: Engineering::Civil engineering; Granger Causal; Neural Network
• Online Access: https://hdl.handle.net/10356/160638
• Institution: Nanyang Technological University

Air passenger forecasting provides important insights for both Governments and Aerospace industries to plan their for their future activities. Google Trends can provide a large database of historical search query frequency which can be used as explanatory variables for air passenger forecasting. Thi...