交通运输工程与信息学报2016，Vol.14Issue(2)：122-127,136,7.DOI:10.3969/j.issn.1672-4747.2016.02.017
基于多维灰色Elman神经网络的国内旅游需求预测
Domestic Tourism Demand Estimation Based on Multi-dimensional Gray Elman Neural Network
褚鹏宇 1刘澜1
作者信息
- 1. 西南交通大学,交通运输与物流学院,成都 610031
- 折叠
摘要
Abstract
In view of the tourism market characteristics influenced by many factors, nonlinear and small-sample data, this paper combines grey theory with Elman neural network to set up a multi-factor estimation model. On the basis of analyzing and selecting the related factors of domestic tourism demand,the per capita disposable income, net income of the rural residents and number of lodging and catering enterprises were determined as the key influence factors with a grey relation method, meanwhile, taking the number of domestic tourism as the characteristic variables, a GM(1,4) model was built. In order to improve the prediction performance of theGM(1,N) model for nonlinear dynamic system, Elman neural network was used to search for the nonlinear mapping relationship between input and output variables. The experimental results show that the combined forecasting model has higher prediction accuracy than the single model, and is applicable to domestic tourism demand prediction.关键词
灰色理论/Elman神经网络/国内旅游需求/多因素预测Key words
Gray theory/Elman neural network/domestic tourism demand/multi-factor prediction分类
管理科学引用本文复制引用
褚鹏宇,刘澜..基于多维灰色Elman神经网络的国内旅游需求预测[J].交通运输工程与信息学报,2016,14(2):122-127,136,7.
