Research on Chengdu air cargo forecast based on improved ARIMA-GARCH Online publication date: Mon, 02-Aug-2021
by Hu Xueqin; Jia Ruimin; Wang Yaqi
International Journal of Modelling in Operations Management (IJMOM), Vol. 8, No. 3, 2021
Abstract: With the transformation of China's economic growth mode and the upgrading of industrial structure, aviation logistics is becoming a strategic industry for China's economic and social development. Accurately predicting the dynamic trend of air cargo volume plays an important role in China's aviation logistics planning and construction, which will promote China's economic and social sustainable development. Due to the long-term trend, seasonal effect and uncertainty characteristics of air cargo volume, a single prediction model can not fit the trend of air cargo volume better, resulting in lower prediction accuracy. In this paper, based on the improved ARIMA-GARCH model, the Chengdu air cargo volume prediction model is established. In which, based on the ARIMA-GARCH model, the default white noise sequence in the GARCH model is replaced by the distribution estimated by the Bootstrap algorithm, thus improving the model's prediction precision.
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