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Please use this identifier to cite or link to this item: http://hdl.handle.net/11129/5249

Title: Fuzzy Rule-Based Intelligent System for Predicting Hotel Occupancy
Authors: Aliyev, Rashad
Salehi, Sara
Eastern Mediterranean University, Faculty of Arts and Sciences, Dept. of Mathematics
Keywords: Mathematics
Applied Mathematics and Computer Science
Forecasting
Time series
Fuzzy c-means clustering
Fuzzy rule-based system
Mamdani model
Issue Date: 2020
Publisher: Eastern Mediterranean University (EMU) - Doğu Akdeniz Üniversitesi (DAÜ)
Citation: Salehi, Sara. (2020). Fuzzy Rule-Based Intelligent System for Predicting Hotel Occupancy. Thesis (Ph.D.), Eastern Mediterranean University, Institute of Graduate Studies and Research, Dept. of Mathematics, Famagusta: North Cyprus.
Abstract: Accuracy and interpretability have always been significant issues in forecasting methods, and it is very important to have a balance between these issues when developing a system in tourism demand forecasting. There are various clustering algorithms used in many branches. The efficiency of the clustering technique is stipulated by the performance of the clustering results. Fuzzy c-means algorithm is highly efficient for unbiased clustering. In this thesis, fuzzy cmeans algorithm is applied on monthly number of guest arrivals in one of the hotels of North Cyprus over 40 months to find the optimal number of clusters in the analysis problem. Also, the fuzzy rule-based system model for hotel occupancy forecasting is developed, and in order to enhance the comprehensibility and accuracy of this model, Mamdani fuzzy rule-based system is used. 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 forecasting model with 7 clusters and 4 inputs provides an optimal solution of the problem. Keywords: Forecasting, Time series, Fuzzy c-means clustering, Fuzzy rule-based system, Mamdani model
OZ: Do˘gruluk ve yorumlanabilirlik, ¨ong¨or¨ulme y¨ontemlerinde her zaman ¨onemli konular olmus¸tur ve bu konular arasında dengeyi sa˘glamak, turizm talebinin ¨ong¨or¨ulmesi ic¸in sistemin gelis¸tirilmesinde c¸ok ¨onemlidir. Birc¸ok alanda kullanılan c¸es¸itli k¨umeleme algoritmaları mevcuttur. K¨umeleme tekni˘ginin verimlili˘gi k¨umeleme sonuc¸larının performansı ile belirlenir. Bulanık c-ortalama algoritması tarafsız k¨umeleme ic¸in y¨uksek verimlili˘ge sahiptir. Bu tezde, bulanık c-ortalama algoritması, 40 ay boyunca Kuzey Kıbrıs’taki otellerden birine gelen misafir sayısı ic¸in uygulanır ve bu algoritmanın amacı, analiz probleminde k¨umelerin en uygun sayısını bulmaktır. Ayrıca, bulanık kural tabanlı sistem modeli, otel doluluk oranını tahmin etmek ic¸in gelis¸tirilir ve bu modelin anlas¸ılırlı˘gını ve do˘grulu˘gunu arttırmak ic¸in Mamdani kural tabanlı sistem kullanılır. Tahmin do˘gruluk ¨olc¸ ¨um¨u ic¸in kullanılan ¨olc¸evler olan hataların ortalama kare k¨ok¨u ve ortalama mutlak y¨uzde hatalarının de˘gerlerine dayanarak, 7 k¨umeli ve 4 giris¸li tahmin modeli problemin en uygun c¸ ¨oz¨um¨un¨un sa˘glanmasını tanımlar. Anahtar Kelimeler: Tahmin, Zaman serisi, Bulanık c-ortalama k¨umeleme, Bulanık kural tabanlı sistem, Mamdani modeli
Description: Doctor of Philosophy in Applied Mathematics and Computer Science. Thesis (Ph.D.)--Eastern Mediterranean University, Faculty of Arts and Sciences, Dept. of Mathematics, 2020. Supervisor: Prof. Dr. Rashad Aliyev.
URI: http://hdl.handle.net/11129/5249
Appears in Collections:Theses (Master's and Ph.D) – Mathematics

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