Open Access. Powered by Scholars. Published by Universities.®
Articles 1 - 2 of 2
Full-Text Articles in Meteorology
Impact Of Weather Factors On Airport Arrival Rates: Application Of Machine Learning In Air Transportation, Robert W. Maxson, Dothang Truong, Woojin Choi
Impact Of Weather Factors On Airport Arrival Rates: Application Of Machine Learning In Air Transportation, Robert W. Maxson, Dothang Truong, Woojin Choi
Publications
Weather is responsible for approximately 70% of air transportation delays in the National Airspace System, and delays resulting from convective weather alone cost airlines and passengers millions of dollars each year due to delays that could be avoided. This research sought to establish relationships between environmental variables and airport efficiency estimates by data mining archived weather and airport performance data at ten geographically and climatologically different airports. Several meaningful relationships were discovered from six out of ten airports using various machine learning methods within an overarching data mining protocol, and the developed models were tested using historical data.
Hyper-Local Weather Predictions With The Enhanced General Urban Area Microclimate Predictions Tool, Kevin A. Adkins, William Becker, Sricharan Ayyalasomayajula, Steven Lavenstein, Kleoniki Vlachou, David Miller, Marc Compere, Avinash Muthu Krishnan, Nickolas Macchiarella
Hyper-Local Weather Predictions With The Enhanced General Urban Area Microclimate Predictions Tool, Kevin A. Adkins, William Becker, Sricharan Ayyalasomayajula, Steven Lavenstein, Kleoniki Vlachou, David Miller, Marc Compere, Avinash Muthu Krishnan, Nickolas Macchiarella
Publications
This paper presents enhancements to, and the demonstration of, the General Urban area Microclimate Predictions tool (GUMP), which is designed to provide hyper-local weather predictions by combining machine-learning (ML) models and computational fluid dynamic (CFD) simulations. For the further development and demonstration of GUMP, the Embry–Riddle Aeronautical University (ERAU) campus was used as a test environment. Local weather sensors provided data to train ML models, and CFD models of urban- and suburban-like areas of ERAU’s campus were created and iterated through with a wide assortment of inlet wind speed and direction combinations. ML weather sensor predictions were combined with best-fit …