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Sara Salehi
Department of Mathematics, Faculty of Arts and Sciences, Eastern Mediterranean University, Famagusta 99628, North Cyprus, via Mersin 10, Turkey

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Journal article
Published: 02 February 2019 in Sustainability
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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.

ACS Style

Rashad Aliyev; Sara Salehi; Rafig Aliyev. Development of Fuzzy Time Series Model for Hotel Occupancy Forecasting. Sustainability 2019, 11, 793 .

AMA Style

Rashad Aliyev, Sara Salehi, Rafig Aliyev. Development of Fuzzy Time Series Model for Hotel Occupancy Forecasting. Sustainability. 2019; 11 (3):793.

Chicago/Turabian Style

Rashad Aliyev; Sara Salehi; Rafig Aliyev. 2019. "Development of Fuzzy Time Series Model for Hotel Occupancy Forecasting." Sustainability 11, no. 3: 793.