Combination forecasts of tourism demand with machine learning models
نویسندگان
چکیده
منابع مشابه
Combination Forecasts of Tourism Demand
This study investigates the performance of combination forecasts in the context of international tourism demand. Five econometric and two time-series models are employed to generate individual forecasts. Six combination methods are then employed, and their forecasting performance evaluated, using data on UK outbound tourism demand in seven destination countries. The results suggest that combina...
متن کاملCombination of Long Term and Short Term Forecasts, with Application to Tourism Demand Forecasting
∗Submitted to International Journal of Forecasting, December 2008. Accepted, and is expected to appear by the end of 2010.
متن کاملDeveloping tourism demand forecasting models using machine learning techniques with trend, seasonal, and cyclic components
This paper proposes the deterministic generation of auxiliary variables, which outline the seasonal, cyclic and trend components of the time series associated with tourism demand for the machine learning models. To test the contribution of the deterministically generated auxiliary variables, we have employed multilayer perceptron (MLP) regression, and support vector regression (SVR) models, whi...
متن کاملBayesian Models for Tourism Demand Forecasting
This study extends the existing forecasting accuracy debate in the tourism literature by examining the forecasting performance of various vector autoregressive (VAR) models. In particular, this study seeks to ascertain whether the introduction of the Bayesian restrictions (priors) to the unrestricted VAR process would lead to an improvement in forecasting performance in terms of achieving a hig...
متن کاملA Machine Learning Approach to Define Weights for Linear Combination of Forecasts
The linear combination of forecasts is a procedure that has improved the forecasting accuracy for different time series. In this procedure, each method being combined is associated to a numerical weight that indicates the contribution of the method in the combined forecast. We present the use of machine learning techniques to define the weights for the linear combination of forecasts. In this p...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Applied Economics Letters
سال: 2015
ISSN: 1350-4851,1466-4291
DOI: 10.1080/13504851.2015.1078441