期刊名称：Journal of Information and Organizational Sciences
印刷版ISSN：1846-3312
电子版ISSN：1846-9418
出版年度：2022
卷号：46
期号：1
页码：157-172
语种：English
出版社：Faculty of Organization and Informatics University of Zagreb
摘要：Forecasting the future trends is of utmost importance for managers and decision makers in different sectors. Scholars thus have introduced various techniques to the service industry aiming at employing a prediction model with ultimate accuracy and high efficiency. The literature proves that adaptive neuro-fuzzy inference systems (ANFIS) are the most efficiency models. However, the literature lacks reports on how ANFIS parameters may affect the accuracy of the system. Employing tourist arrival records to Cyprus between 2015 and 2019, this study has developed an ANFIS system to evaluate the accuracy performance of different prediction models with varied number of inputs and number or type of membership functions. Results show that the forecasting accuracy of a model with four inputs and four membership functions when the type of membership functions is Gaussian is relatively better than other models. In other words, it can be concluded that the forecast model with four inputs and four Gaussian membership functions is ultimate with the most accurate prediction record with reference to MAE, RMSE, and MAPE. The results of this study may be significant for senior managers and decision-makers of the tourism industry.
