Airline Economics

Zhang, Anming; Zhang, Yahua; Zhi-bin, Huang

doi:10.1016/b978-0-08-102671-7.10074-0

Cited by 2 publications

(1 citation statement)

References 26 publications

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“…(Sun, Wandelt, and Zhang 2021;Liu et al 2019;Zhang, Wan, and Yang 2019). However, we can expect that flight demand will be substantially increased as air transport retains a major role in long-term aviation economic (Zhang, Zhang, and Huang 2021). The aviation community is attempting to find different eco-friendly approaches, including emissions trading system (Hamaguchi 2021;Girardet and Spinler 2013), incentive and penalty-based aviation emission regulation and control (Liao et al 2021), alternative fuels (Zhang, Fang, et al 2020;Goding, Andersson-Franko, and Lagerkvist 2018) and efficient aircraft design (Santos and Delina 2021), to reduce the levels of aviation emission.…”

Section: Problem Descriptionmentioning

confidence: 99%

Emission-aware adjustable robust flight path planning with respect to fuel and contrail cost

2022

Transportmetrica B: Transport Dynamics

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Aviation emission has always been regarded as the major contributor to climate and atmosphere changes. The recent research suggested that flights can be re-routed from sufficiently cold and humid atmospheres to mitigate the level of contrail production in particular regions during the flight planning stage. To address the needs, a weather data-driven flight path planning is proposed in this work. The spatial meteorological condition is generated using historical data and formulated as uncertain factors to develop a robust solution. Airlines can determine their allowance of flight level changes, pre-determined constrained flight levels set and robustness towards the maximum tolerance level of uncertain contrail length of a flight path. The overall cost can be further minimised, with a lowered total contrail length with the least increases in fuel consumption cost. The suggested methods validate the possibility of emission-aware adjustable robust flight path planning and ensure sustainable air transport operations.

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Section: Problem Descriptionmentioning

confidence: 99%

Emission-aware adjustable robust flight path planning with respect to fuel and contrail cost

2022

Transportmetrica B: Transport Dynamics

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Comparison of Artificial Intelligence Techniques for The UK Air Passenger Short-Term Demand Forecasting: A Destination Insight Study

KOÇAK

2023

Journal of Aviation

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Web search queries become essential drivers to forecast air passenger demand for operational benefits. Scholars and marketing experts. Forecasting passenger demand is one of the most important marketing problems that experts frequently encounter, but there are very few studies in the literature using search queries. The main novelty of this study is to show that Destination Insight (DI) can be useful as an air passenger demand proxy in the UK. To prove this primary objective, this work uses several machine and deep learning multi layer perceptron (MLP) methods based on a big-data framework. The findings indicate that DI is a crucial predictor of the UK air passenger demand. Besides, various error metrics (e.g., RMSE, MAPE, MAD) were compared to find the best model in this study. Specifically, results indicate that MLP following feed forward neural networks works better for the UK air passenger market.

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Airline Economics

Cited by 2 publications

References 26 publications

Emission-aware adjustable robust flight path planning with respect to fuel and contrail cost

Emission-aware adjustable robust flight path planning with respect to fuel and contrail cost

Comparison of Artificial Intelligence Techniques for The UK Air Passenger Short-Term Demand Forecasting: A Destination Insight Study

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