Predication Method for China’s Civil Aviation Fuel Consumption

Qian CAO, Runtian JING, Jun ZHANG, Ju BAI


With the China’s civil aviation industry gradual market-oriented and the rapid development of China’s economy, China’s civil aviation transportation fuel consumption has grown significantly in nearly past three decades. Therefore, it’s a very important strategic significance of the prediction of China’s civil aviation transportation fuel consumption. In this paper, gray system and neural network approach, combined with China’s civil aviation industry 1980-2010 total traffic volume of the data, we establish gray system GM (1,1) model and BP neural network model for civil aviation transport volume. Training and simulation of the back propagation neutral network model and the gray system GM(1,1) used MATLAB. BP neural network modeling takes into account in three factors: the number of aircraft aviation industry, flight hours and total turnover. The fitting precision of the gray system GM(1,1) model is 64.2% while the fitting precision of the back propagation neutral network model is 90.16%. Thus, the back propagation neutral network model is better for estimating Civil aviation fuel consumption.


China’s civil aviation industry; Fuel consumption; BP neural network; GM(1,1)

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