Research on Air Logistics Demand Forecasting Based on Induced Ordered Weighted Geometric Averaging Operator
Guangzhou Baiyun International Airport,as an important air cargo hub,has witnessed rapid growth in air logistics demand.To accurately forecast the future air logistics demand of Guangzhou Baiyun International Airport,this study applies the Triple Exponential Smoothing method and the Grey GM(1,1)model as forecasting tools and constructs a combination forecasting model based on the Induced Ordered Weighted Geometric Averaging(IOWGA)operator.An empirical analysis of the cargo volume data of Guangzhou Baiyun International Airport during 2009 to 2023 reveals that the combination forecasting model outperforms single models in terms of forecasting accuracy and error.The forecasting results indicate that theair cargo volume of Guangzhou Baiyun International Airport will continue to grow,reaching 2 302 800 tons by 2028.The study demonstrates that the combination forecasting model can more accurately reflect the development trend of air logistics demand of Guangzhou Baiyun International Airport,and provides an effective modeling and forecasting approach and important reference for air logistics demand forecasting.
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