[[abstract]]Fuzzy time series model has been developed to either improve forecasting accuracy or reduce computation time, whereas a residul analysis in order to improve its forecasting performance is still lack of consideration. In this paper, we propose a novel Fourier method to revise the analysis of residual terms, and then we illustrate it to forecast the Japanese tourists visiting in Taiwan per year. The forecasting results show that our proposed method can derive the best forecasting performance as well as the smallest forecasting error of MAPE in the training sets; in the testing sets, the proposed model is also better to fit the future trend than some forecasting models.[[incitationindex]]EI[[ispeerreviewed]]Y[[booktype]]電子版[[bookty...
Machine learning is a branch of artificial intelligence where machines are designed to learn on thei...
The purpose of this study is to propose whether an average-based fuzzy time series model is appropri...
Many forecasting models based on the concepts of fuzzy time series have been proposed in the past de...
Problem statement: Forecasting is very important in many types of organizations since predictions of...
In several applications, fuzzy time series forecasting was utilized to generate predictions about th...
Forecasting has been considered important in a service industry. Many techniques have been applied t...
100學年度研究獎補助論文[[abstract]]In this study, an adaptivefuzzytimeseriesmodel for forecasting Taiwan’stour...
Forecasting has been considered important in a service industry. Many techniques have been applied t...
AbstractTourism demand forecasting has attracted substantial interest because of the significant eco...
Literature reviews show that the most commonly studied fuzzy time series models for the purpose of f...
AbstractTourism demand forecasting has attracted substantial interest because of the significant eco...
Tourism demand forecasting has attracted substantial interest because of the significant economic co...
This study develops a model to forecast inbound tourism to Japan, using a combination of artificial ...
Various forecast models can be adopted for predicting what types of tourism demand are vulnerable to...
The purpose of this study is to propose whether an average-based fuzzy time series model is appropri...
Machine learning is a branch of artificial intelligence where machines are designed to learn on thei...
The purpose of this study is to propose whether an average-based fuzzy time series model is appropri...
Many forecasting models based on the concepts of fuzzy time series have been proposed in the past de...
Problem statement: Forecasting is very important in many types of organizations since predictions of...
In several applications, fuzzy time series forecasting was utilized to generate predictions about th...
Forecasting has been considered important in a service industry. Many techniques have been applied t...
100學年度研究獎補助論文[[abstract]]In this study, an adaptivefuzzytimeseriesmodel for forecasting Taiwan’stour...
Forecasting has been considered important in a service industry. Many techniques have been applied t...
AbstractTourism demand forecasting has attracted substantial interest because of the significant eco...
Literature reviews show that the most commonly studied fuzzy time series models for the purpose of f...
AbstractTourism demand forecasting has attracted substantial interest because of the significant eco...
Tourism demand forecasting has attracted substantial interest because of the significant economic co...
This study develops a model to forecast inbound tourism to Japan, using a combination of artificial ...
Various forecast models can be adopted for predicting what types of tourism demand are vulnerable to...
The purpose of this study is to propose whether an average-based fuzzy time series model is appropri...
Machine learning is a branch of artificial intelligence where machines are designed to learn on thei...
The purpose of this study is to propose whether an average-based fuzzy time series model is appropri...
Many forecasting models based on the concepts of fuzzy time series have been proposed in the past de...