摘要
根据组合预测的理论和神经网络的非线性和良好的函数逼近特性,提出了基于人工神经网络的灰色幂模型、多项式回归模型组合的航空客运量预测模型.此模型综合了各单一模型的有效信息,同时也融合了人工神经网络在不确定因素预测领域的优势,能够比较客观地反映我国航空客运系统的发展趋势.文末通过实例对模型精度进行了分析,结果表明,预测值与实际结果具有良好的一致性..
In this paper , grey-regression combination forecasting model based on BP neural networks for air passenger capacity is given ,which is nonlinear and has excellent feature of function approximation. It takes full advantages of effective information of combined models and advantages in uncertain factor forecasting of artificial neural network. So it can reflect the objective trend of system of air passenger capacity. Case study validates the effectiveness of the proposed model.
出处
《沈阳理工大学学报》
CAS
2008年第3期82-85,共4页
Journal of Shenyang Ligong University
关键词
航空客运量
组合预测
GM(1
1)幂模型
回归模型
BP神经网络
air passenger capacity
combinatorial forecasting
GM （ 1,1 ） power model
re- gression model
BP neural networks
