Forecasting of a Non-Seasonal Tourism Time Series with ANN

被引：0

作者：

Teixeira, Joao Paulo ^{[1
,2
]}

Fernandes, Paula Odete ^{[1
,2
]}

机构：

[1] Polytech Inst Braganca, Braganca, Portugal

[2] UNIAG, Viana Do Castelo, Portugal

来源：

INTERNATIONAL WORK-CONFERENCE ON TIME SERIES (ITISE 2014) | 2014年

关键词：

ANN; Forecast; Non-seasonal time series; Tourism; Cape Verde; DEMAND;

D O I：

暂无

中图分类号：

F [经济];

学科分类号：

02 ;

摘要：

The paper present and discusses several alternative architectures of Artificial Neural Network models used to predict the time series of tourism demand for Cape Verde. This time series is particularly difficult to predict due to its non-seasonal characteristic usual in a similar time series for European Tourism destinations. The time index used as input and other input parameters variations improved the performance of the prediction over the test set to a relative error of 7.3% and a Pearson correlation coefficient of 0.92.

引用

页码：724 / 734

页数：11

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