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新型组合预测模型在空中交通流量预测的应用 被引量:3

New Combined Forecasting Model Applied in Air Traffic Flow Forecast
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摘要 民航运输业的快速发展使空中交通流量迅猛增加,如何准确预测未来的交通流量是关乎到行业资源高效分配、战略合理部署的一个重要问题。因此,国内外众多专家对空中交通流量的预测进行了大量研究,提出了诸多模型和方法。针对目前空中交通流量预测中存在的缺陷与不足,提出并建立了一种适用于民航的新型组合预测模型。将趋势外推法拟合的结果作为多元回归分析法的复合时间变量组,并利用主成份分析法实现了复合时间变量组与其他影响因素变量的有机结合,建立了趋势外推法和多元回归分析法的组合预测模型。以上海终端区的空中交通流量预测为例,借助SPSS数据统计软件进行研究分析,通过对预测结果的各项精度检验,与传统方法相比较,证实本预测模型的优越性。 The quick development of civil aviation transport industry makes the air traffic flow increase rapidly. How to forecast the future traffic volume accurately is the key issue of the efficient allocation of industry resources and reasonable disposition strategy. So a lot of domestic and foreign experts do research on the forecast of air traffic flow and put forward a number of models and methods. This paper proposes and constructs a new combined forecasting model applied in civil aviation industry, considering the defects of the current air traffic flow forecasting. This model takes the results of trend extrapolation as the composite time variables of multiple tegression analysis. Referring to the principle component analysis, the model successfully combines the composite time variables and the other effect factor variables, then establishes a new combined forecasting model of trend extrapolation and multiple regression analysis. Taking the example of SHA terminal control area, by means of SPSS (statistical product and service solutions) soft, the check result of forecasting precision which is compared to the traditional forecasting models verifies the effectiveness of the new combination forecasting model proposed.
出处 《中国民航大学学报》 CAS 2009年第5期4-8,共5页 Journal of Civil Aviation University of China
基金 国家空管委基金项目(GKG200802015)
关键词 主成份分析法 趋势外推法 多元回归分析 空中交通流量 组合预测 principle component analysis trend extrapolation multiple regression analysis air traffic flow combined forecasting
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共引文献30

同被引文献18

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