HHC-Article

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Browsing HHC-Article by Subject "airlines"

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    The use of an artificial neural network to predict Australia’s export air cargo demand
    (International Journal for Traffic and Transport Engineering (IJTTE), 2018) Glenn Baxter; Panarat Srisaeng
    In this paper an Artificial Neural Network (ANN) is proposed for predicting Australia’s annual export air cargo demand. The modelling in the study was based on annual data from 1993 to 2016. The ANN model was developed using the input parameters of world real merchandise exports, world population growth, world jet fuel prices, world air cargo yields (proxy for air cargo costs), outbound flights from Australia, and Australian/United States dollar exchange rate and two dummy variables, which controlled for the strong cyclical fluctuations in air cargo demand which occurred in 2003 and 2015. The artificial neural network (ANN) used multi-layer perceptron (MLP) architecture that compromised a multi-layer feed-forward network and the sigmoid and linear functions were used as activation functions with the feed forward-back propagation algorithm. The ANN was applied during training, testing and validaion and had 8 inputs, 1 neuron in the hidden layer and 1 neuron in the output layer. The data was randomly divided into three data sets; training, testing and model validation. The best-fit model was selected according to four goodness-of-fit measures: mean absolute error (MAE), mean square error(MSE), root mean square errors (RMSE), and mean absolute percentage errors (MAPE). The highest R-value obtained from the ANN model is 0.97844. The results suggest that the ANN model is an efficient tool for predicting Australia’s annual export air cargo demand.
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    The Use of Aviation Biofuels as an Airport Environmental Sustainability Measure: The Case of Oslo Gardermoen Airport
    (Magazine of Aviation Development, 2020-03-29) Glenn Baxter; Panarat Srisaeng; Graham Wild
    In recent times, there has been a growing trend by airports and airlines to use aviation biofuel as an environment sustainability measure. Using an instrumental qualitative case study research design, this paper examines the evolution of sustainable aviation fuels at Oslo Airport Gardermoen. Oslo Airport Gardermoen was the first airport in the world to offer the first airport in the world to offer aviation biofuels to all airlines in 2016. The qualitative data were examined by document analysis. The study found that the use of sustainable aviation biofuels has delivered tangible environmental benefits to Oslo Gardermoen Airport. The usage of aviation biofuels has enabled the airport, and the airlines using sustainable aviation biofuels, to reduce their greenhouse gases by 10-15%. Also, as part of Norway’s efforts to reduce greenhouse gas emissions, the Norwegian Government have mandated that the aviation fuel industry must mix 0.5% advanced biofuel into jet fuel from 2020 onwards. Norway’s Ministry of Climate and Environment’s goal is that by 2030, 30% of the airline fuel will be sustainable in nature and will have a positive climate effect. Avinor, the operator of Norway’s airports, has a goal that by 2030, 30 % of aviationfuel supplied in Norway should be sustainable biofuel – this follows the Norwegian government’s mandate.