Abstract: On the basis of the historical data of air cargo volume in China and its influence factors, such as worker average wage, GDP per capita and GDP, consumer spending, routes, the social fixed assets investment and population, through application of GM（1，1）, multi-regression model and a combination prediction model based on IOWHA（Induced Ordered Weighted Harmonic Averaging） operators for forecasting the air cargo volume, the study shows the model given in this paper is effective and reasonable, has higher forecasting accuracy and can be used to predict the air cargo volume in China.

Key words: multi-regression, grey model（1, 1）, Induced Ordered Weighted Harmonic Averaging（IOWHA） operator, air cargo volume

摘要： 收集我国民航货运量及其影响要素（职工平均工资、人均GDP、GDP、人均消费支出、航线里程、全社会固定资产投资和人口数量）的统计数据为基础，应用多元回归模型和GM（1，1）模型对样本数据进行分别预测，以此为基础，指出引入诱导有序调和加权平均算子（IOWHA）进行组合预测的必要性，基于该算子的优化组合模型进行预测，并构建误差评价指标体系。结果表明，基于诱导有序调和加权平均算子的民航货运量预测的各项误差指标值均低于任一单项预测值，说明该组合预测模型的预测效果更佳，预测精度更高，可应用于实际预测。

关键词: 多元回归, GM（1, 1）, 诱导有序调和加权平均（IOWHA）算子, 民航货运量