作者
Ying Yu, Yirui Wang, Shangce Gao, Zheng Tang
发表日期
2017
期刊
Computational intelligence and neuroscience
卷号
2017
期号
1
页码范围
7436948
出版商
Hindawi Publishing Corporation
简介
With the impact of global internationalization, tourism economy has also been a rapid development. The increasing interest aroused by more advanced forecasting methods leads us to innovate forecasting methods. In this paper, the seasonal trend autoregressive integrated moving averages with dendritic neural network model (SA‐D model) is proposed to perform the tourism demand forecasting. First, we use the seasonal trend autoregressive integrated moving averages model (SARIMA model) to exclude the long‐term linear trend and then train the residual data by the dendritic neural network model and make a short‐term prediction. As the result showed in this paper, the SA‐D model can achieve considerably better predictive performances. In order to demonstrate the effectiveness of the SA‐D model, we also use the data that other authors used in the other models and compare the results. It also proved that …
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