基于多种模型的浙江省入境游客量预测

A Forecast on the Inbound Tourist Amount of Zhejiang Province Using Multiple Models

入境游客量是衡量地区旅游发展的重要指标之一,准确的旅游需求预测可以为旅游规划提供参考依据。本文根据浙江省2001-2011年接待入境旅游游客量及其他相关统计数据,运用BP神经网络法、GMDH模型、逐步回归分析与BP神经网络组合预测法以及BP神经网络与GMDH模型组合预测法,基于影响因子要素对入境游客量进行预测分析。实验证明BP神经网络与GMDH模型组合预测法具有较强的预测优势。

The inbound tourist amount is an important indicator of measuring regional tourism development, accurate tourists demand forecast can provide a reference for tourism planning. According to the statistical data during the period of 2001-2011 about the number of inbound tourists received in Zhejiang, and by using BP neural network, GMDH model, combinatorial prediction model of stepwise regression analysis and BP neural network, combinatorial prediction model of BP neural network and GMDH, the inbound tourist amount was forecasted based on influencing factors. Results showed that combinatorial prediction model of BP neural network and GMDH had strong predictive advantage.