Artificial Neural Network Models for Forecasting Tourist Arrivals to Barcelona

Date

2016-09-09

Author

Alptekin, Bülent
ALADAĞ, ÇAĞDAŞ HAKAN

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In order to reach accurate tourism demand forecasts, various forecasting methods have been proposed in the literature [1]. These approaches can be divided into two subclasses. One of them is conventional methods such as autoregressive moving average (ARIMA) or exponential smoothing. And, the other one is advanced forecasting techniques such as fuzzy time series, artificial neural networks (ANN) or hybrid approaches. The main purpose of this study is to develop some efficient forecasting models based on ANN for tourism demand of Barcelona in order to reach high accuracy level.

Subject Keywords

Forecasting, Time series, Feed forward neural networks

URI

https://hdl.handle.net/11511/56220

Conference Name

25th International Conference on Artificial Neural Networks (ICANN)

Collections

Department of Statistics, Conference / Seminar

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Citation Formats

B. Alptekin and Ç. H. ALADAĞ, “Artificial Neural Network Models for Forecasting Tourist Arrivals to Barcelona,” Barcelona, Spain, 2016, vol. 9886, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/56220.