This paper develops tourism demand econometric models based on the monthly data of tourists to Taiwan and adopts Multivariate Adaptive Regression Splines (MARS), Artificial Neural Network (ANN) and Support Vector Regression (SVR), MARS, ANN and SVR to develop forecast models and compare the forecast results. The results showed that SVR model is the optimal model, with a mean error rate of 3.61%, ANN model is the sub-optimal model, with a mean error rate of 7.08%, and MARS is the worst model, with a mean error rate of 11.26%. JEL classification numbers: M3
This study is aimed to model and forecast the tourism demand for Mozambique for the period from Jan...
AbstractTourism demand forecasting has attracted substantial interest because of the significant eco...
Forecasting has been considered important in a service industry. Many techniques have been applied t...
As one of the important areas in tourism research, tourism demand modeling and forecasting have been...
[[abstract]]Support vector machines (SVMs) have been successfully applied to solve nonlinear regress...
The global tourism industry has witnessed a significant growth in the past few decades. Many researc...
This paper investigates the combination of individual forecasting models and their roles in improvin...
Various forecast models can be adopted for predicting what types of tourism demand are vulnerable to...
[[abstract]]Accurate prediction of tourism demand is a crucial issue for the tourism and service ind...
This research examines and proves this effectiveness connected with artificial neural networks (ANNs...
China has experienced a massive growth in international tourism over the past two decades. To date, ...
Forecasting plays a major role in tourism planning. The promotion of tourism projects involving subs...
This study compares the performance of different Artificial Neural Networks models for tourist deman...
To improve the forecasting accuracy of tourism demand through forecasting model and data sources, th...
An econometric model is very useful to understand relationships among economic variables such as tou...
This study is aimed to model and forecast the tourism demand for Mozambique for the period from Jan...
AbstractTourism demand forecasting has attracted substantial interest because of the significant eco...
Forecasting has been considered important in a service industry. Many techniques have been applied t...
As one of the important areas in tourism research, tourism demand modeling and forecasting have been...
[[abstract]]Support vector machines (SVMs) have been successfully applied to solve nonlinear regress...
The global tourism industry has witnessed a significant growth in the past few decades. Many researc...
This paper investigates the combination of individual forecasting models and their roles in improvin...
Various forecast models can be adopted for predicting what types of tourism demand are vulnerable to...
[[abstract]]Accurate prediction of tourism demand is a crucial issue for the tourism and service ind...
This research examines and proves this effectiveness connected with artificial neural networks (ANNs...
China has experienced a massive growth in international tourism over the past two decades. To date, ...
Forecasting plays a major role in tourism planning. The promotion of tourism projects involving subs...
This study compares the performance of different Artificial Neural Networks models for tourist deman...
To improve the forecasting accuracy of tourism demand through forecasting model and data sources, th...
An econometric model is very useful to understand relationships among economic variables such as tou...
This study is aimed to model and forecast the tourism demand for Mozambique for the period from Jan...
AbstractTourism demand forecasting has attracted substantial interest because of the significant eco...
Forecasting has been considered important in a service industry. Many techniques have been applied t...