Development of Fuzzy Time Series Model for Hotel Occupancy Forecasting

Rashad Aliyev, Sara Salehi and Rafig Aliyev
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Rashad Aliyev: Department of Mathematics, Faculty of Arts and Sciences, Eastern Mediterranean University, Famagusta 99628, North Cyprus, via Mersin 10, Turkey
Sara Salehi: Department of Mathematics, Faculty of Arts and Sciences, Eastern Mediterranean University, Famagusta 99628, North Cyprus, via Mersin 10, Turkey
Rafig Aliyev: Warwick Business School, University of Warwick, Coventry CV4 7AL, UK

Sustainability, 2019, vol. 11, issue 3, 1-13

Abstract: 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.

Keywords: time series; forecasting; fuzzy c-means clustering; fuzzy rule-based system; Mamdani model (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (4)

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