FORECASTING INTERNATIONAL AIRLINE PASSENGER TRAFFIC USING NEURAL NETWORKS

被引：0

作者：

NAM, K

SCHAEFER, T

机构：

来源：

LOGISTICS AND TRANSPORTATION REVIEW | 1995年 / 31卷 / 03期

关键词：

D O I：

暂无

中图分类号：

C93 [管理学]; O22 [运筹学];

学科分类号：

070105 ; 12 ; 1201 ; 1202 ; 120202 ;

摘要：

This paper examines the potential of using neural networks (NNs) in lieu of traditional statistical techniques in forecasting international airline passenger traffic. Neural networks appear to enhance forecasting accuracy and go beyond the capabilities of conventional statistical analysis. Therefore, airline decision makers should benefit from using neural networks in forecasting airline passenger loads.

引用

页码：239 / 251

页数：13

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