Knowing aircraft taxi-time precisely a-priori is increasingly important for any airport management system. This work presents a new approach for estimating and characterising the taxi-time of an aircraft based on historical information. The approach makes use of the interval type-2 fuzzy logic system, which provides more robustness and accuracy than the conventional type-1 fuzzy system. To compensate for erroneous modelling assumptions, the error distribution of the model is further analysed and an error compensation strategy is developed. Results, when tested on a real data set for Manchester Airport (U.K.), show improved taxi-time accuracy and generalisation capability over a wide range of modelling assumptions when compared with existing fuzzy systems and linear regression-based methods.
A type-2 fuzzy modelling framework for aircraft taxi-time prediction
2017-10-01
683086 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
Aircraft taxi time prediction: Feature importance and their implications
Elsevier | 2020
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