模糊线性回归模型在航空客运周转量预测中的应用研究

Study on Forecasting of Air Passenger Turnover with Fuzzy Linear Regression Model

为能准确把握航空客运周转量的未来特征,寻求高精度预测方法是学术界多年致力研究的热点。拟采用模糊线性回归模型预测我国航空客运周转量,并利用因子分析法对该模型及常见预测方法进行评估。评价结果可知:模糊线性回归模型的预测精度不仅高于单因数趋势外推的预测方法(灰色模型、增长率统计法和指数平滑法),也高于多因素综合性预测模型(多元线性回归),说明此模型在预测航空客运周转量的变化中有一定实用价值。

In order to grasp the future characters of air passenger turnover, it is a significant issue how to select a forecast model with higher estimate accuracy at present. The papers build a fuzzy linear regression model between air passenger turnover and relative factors, and forecast air passenger turnover. Then the papers undergo a comprehensive analysis and evaluation to the regression analysis, grey model, growth statistics, exponential smoothing and fuzzy linear regression which predict air passenger turnover by factor analysis. From the evaluative result, it is believed that the prediction precision of fuzzy linear regression method is higher than the other methods, and it can be satisfactorily applied to predict air passenger turnover.