SIE Seminar: Zhijie (Sasha) Dong
October 5th, 2023 - 2 p.m. (MST)
Sasha Dong
Associate Professor
Department of Construction Management
University of Houston
"Flight Delay Prediction with Priority Information of Weather and Non-Weather Features"
ENGR 301 or via Zoom
Abstract: Flight delay prediction is a major topic in intelligent airport management systems, which emphasizes the use of historical data and potential features to estimate whether a future flight will delay. However, many factors affect flight delays, and these factors can be categorized into weather features (e.g., temperature, humidity, and wind speed) and non-weather features (day-of-month, day-of-week, scheduled departure and arrival time). Moreover, the impacts of weather and non-weather factors on flight delays are different. Weather features play a more important role in adverse weather conditions and are the main reason for long flight delays. When the weather condition changes from severe to non-severe, non-weather features are the main reason for flight delays, and the caused delays are relatively short. Such different impacts on flight delays raise a strong need for considering the priority information of weather and non-weather features in flight delay prediction. In this paper, we design a variant of the Random Forest model to consider the priority information of weather and non-weather features to predict flight delays. A clustering algorithm-based analysis approach is developed to assess the impact of weather and non-weather features on flight delays and draw conclusions on the priority information of weather and non-weather features. A probability sampling method is embedded in the Random Forest at the feature selection stage to perform a prior choice for weather and non-weather features to help select the key influential features. Experiments were carried out on U.S. domestic flights in July 2018, and the comparison results demonstrate that the proposed model can significantly increase flight delay prediction accuracy.
Bio: Dr. Zhijie (Sasha) Dong is currently an associate professor in the Department of Construction Management at the University of Houston. She received her Ph.D. degree from Cornell University, master's degree from Columbia University, and bachelor's degree from Nanjing University. Before returning to academia, Dr. Dong worked for FedEx, CSX Transportation, and General Motors. Her research focuses on improving the efficiency of different complex systems (e.g., supply chain and transportation) through optimization and artificial intelligence. Dr. Dong’s work is supported by both federal agencies (e.g., NSF, FHWA, and DOE) and industry (e.g., AMD and Shell). She is the recipient of multiple international and national awards, including the NSF CISE CRII Awards, NSF OSSEEER Early Career Fellow, and the honorable mention of INFORMS MIF Early Carrer Award. Dr. Dong is a senior member of IISE and the president-elect of the IISE Logistics and Supply Chain Division. She also serves on the editorial board of Communications Engineering (Nature Portfolio).