A paired neural network model for tourist arrival forecasting

作者：

Highlights：

• We developed a novel structural neural network (sNN) model for forecasting tourism demand.

• The sNN captures the trend and seasonal patterns of tourism demand accurately.

• Empirical results show a significantly superior performance of sNN to benchmark models.

摘要

•We developed a novel structural neural network (sNN) model for forecasting tourism demand.•The sNN captures the trend and seasonal patterns of tourism demand accurately.•Empirical results show a significantly superior performance of sNN to benchmark models.

论文关键词：Forecasting,Tourism demand,Structural neural network,Low-pass filter

论文评审过程：Received 15 April 2018, Revised 13 August 2018, Accepted 14 August 2018, Available online 16 August 2018, Version of Record 7 September 2018.

论文官网地址：https://doi.org/10.1016/j.eswa.2018.08.025