基于组合预测模型的南京禄口国际机场货运吞吐量预测  

Cargo Throughput Prediction of Nanjing Lukou International Airport Based on Combined Prediction Model

作　　者：王琪[1] 张洪[1] WANG Qi;ZHANG Hong(School of Evergrande Management,Wuhan University of Science and Technology,Wuhan 430000,China)

机构地区：[1]武汉科技大学恒大管理学院,湖北武汉430000

出　　处：《物流工程与管理》2023年第2期83-86,共4页Logistics Engineering and Management

摘　　要：南京禄口国际机场是长三角经济圈的主要货运机场。作为大型国际航空枢纽,其在疫情的冲击下经历了“先抑后扬”的波动式发展阶段。文中基于后疫情时代背景,从南京禄口国际机场航空物流发展现状出发,首先选用熵值法确定了影响航空物流吞吐量的各项指标权重,再结合GA-BP神经网络模型预测机场货运吞吐量,最终得出南京禄口国际机场2022-2030年货运吞吐量预测值。Nanjing Lukou International Airport is the main cargo airport in the Yangtze River Delta economic circle.As a large international aviation hub, it has experienced a fluctuating development stage of “first inhibition and then promotion” under the impact of the epidemic.Based on the background of the post-epidemic era and the development status of aviation logistics at Nanjing Lukou International Airport, entropy method is used to determine the weight of various indicators affecting the throughput of aviation logistics, and then GA-BP neural network model was used to predict the cargo throughput of Nanjing Lukou International Airport.Finally, the predicted value of cargo throughput of Nanjing Lukou International Airport from 2022-2030 was obtained.

关 键 词：货运吞吐量预测 熵值法 遗传算法 BP神经网络 

分 类 号：F562[经济管理—产业经济]