Development of Fuzzy Time Series Model for Hotel Occupancy Forecasting

被引：18

作者：

Aliyev, Rashad ^{[1
]}

Salehi, Sara ^{[1
]}

Aliyev, Rafig ^{[2
]}

机构：

[1] Eastern Mediterranean Univ, Fac Arts & Sci, Dept Math, Via Mersin 10, TR-99628 Famagusta, North Cyprus, Turkey

[2] Univ Warwick, Warwick Business Sch, Coventry CV4 7AL, W Midlands, England

来源：

SUSTAINABILITY | 2019年 / 11卷 / 03期

关键词：

time series; forecasting; fuzzy c-means clustering; fuzzy rule-based system; Mamdani model; TOURISM DEMAND; ENROLLMENTS;

D O I：

10.3390/su11030793

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

摘要：

Receiving appropriate forecast accuracy is important in many countries' economic activities, and developing effective and precise time series model is critical issue in tourism demand forecasting. In this paper, fuzzy rule-based system model for hotel occupancy forecasting is developed by analyzing 40 months' time series data and applying fuzzy c-means clustering algorithm. Based on the values of root mean square error and mean absolute percentage error which are metrics for measuring forecast accuracy, it is defined that the model with 7 clusters and 4 inputs is the optimal forecasting model for hotel occupancy.

引用

页数：13

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