Kubilay ECERKALE, TARIK KÜÇÜKDENİZ, ŞAKİR ESNAF

COMPARISON OF FUZZY TIME SERIES BASED ON DIFFERENCE PARAMETERS AND TWO-FACTOR TIME-VARIANT FUZZY TIME SERIES MODELS FOR AVIATION FUEL PRODUCTION FORECASTING

Zaman serileri üretimde doğru tahminler yapmakta kullanılmaktadır. Bu makalede, deney veri seti olarak Türkiye'nin geçmiş 3 yıllık jet yakıt üretimi miktarları kullanılmıştır. Jet yakıt üretim miktarlarını tahmin edebilmek için parametrelerin farkı bazlı bulanık zaman serisi ile iki faktör zaman değişimli bulanık zaman serisi kullanılmış ve sonuçlar karşılaştırılmıştır. Jet yakıt üretim vakası için her iki bulanık zaman serisi metodunun da uygulamada avantajları ve dezavantajları olduğu sonucuna varılmıştır

JET YAKIT ÜRETİMİ TAHMİNİNDE PARAMETRELERİN FARKI BAZLI BULANIK ZAMAN SERİSİ İLE İKİ FAKTÖR ZAMAN DEĞİŞİMLİ BULANIK ZAMAN SERİSİ METOTLARININ KARŞILAŞTIRMASI

Time series models have been utilized to make accurate predictions in production. This paper employs a 3 year period of aviation fuel production data of Turkey as experimental data set. To forecast the aviation fuel production amounts, fuzzy time series forecasting based on difference parameters and two-factor time-variant fuzzy time series models are used and the results have been compared in this study. Based on the comparison results in the case of aviation fuel production, we conclude that both of the fuzzy time series models have advantages and disadvantages in use

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[1] Yu, T.H.K., Huarng, K.H., 2008, A bivariate fuzzy time series model to forecast the TAIEX, Expert Systems with Applications Volume 34, p. 2945–2952.
[2] Jilani, T.A. and Burney, S.M.A., 2008, A refined fuzzy time series model for stock market forecasting, Physica A, 387, p. 2857–2862.
[3] Yu, H.K., 2005, A refined fuzzy time-series model for forecasting, Physica A, 346, p. 657–681.
[4] Singh, S.R., 2007, A robust method of forecasting based on fuzzy time series, Applied Mathematics and Computation, 188, p. 472–484.
[5] Singh, S.R., 2007, A simple method of forecasting based on fuzzy time series, Applied Mathematics and Computation, 186, p. 330–339.
[6] Huarng, K.H. and Yu, H.K., 2005, A Type 2 fuzzy time series model for stock index forecasting, Physica A, 353, p. 445–462.
[7] Li, S.T. and Cheng, Y.C., 2007, Deterministic fuzzy time series model for forecasting enrollments, Computers and Mathematics with Applications, 53, p. 1904–1920.
[8] Lee, L.W., Wang, L.H. and Chen, S.M., 2007, Temperature prediction and TAIFEX forecasting based on fuzzy logical relationships and genetic algorithms, Expert Systems with Applications, 33, p. 539–550.
[9] Chen, S.M. and Hwang, J.R., 2000, Temperature Prediction Using Fuzzy Time Series, IEEE Transactions On Systems, Man, And Cybernetics—Part B: Cybernetics, Volume 30, No. 2.
[10]Khashei, M. Hejazi, S.R. and Bijari, M., 2008, A new hybrid artificial neural networks and fuzzy regression model for time series forecasting, Fuzzy Sets and Systems, 159, p. 769–786.
[11]Zhang, C., Ma, C., Song, D. and Tian, W., 2007, An Entropy-based Fuzzy Time Series Method for Forecasting Airport Passenger Throughput, Fourth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD).
[12]Tsai, C.C. and Wu, S.J., 1999, A Study for Second-order Modeling of Fuzzy Time Series, 1W9 IEEE International Fuzzy Systems Conkrenee Proceedings, Seoul, Korea.
[13]Wang, C.H. and Hsu, L.C., 2008, Constructing and applying an improved fuzzy time series model: Taking the tourism industry for example, Expert Systems with Applications, 34, p. 2732– 2738.
[14]Wang, C.H., 2004, Predicting tourism demand using fuzzy time series and hybrid grey theory, Tourism Management, 25, p. 367–374.
[15]Zadeh, L.A., 1965, Fuzzy set, Information and Control, 8, p. 338–353.
[16]Zadeh, L.A., 1975, The Concept Of A Linguistic Variable And İts Application To Approximate Reasoning – Part I, Information Sciences, 8, p. 199–249.
[17]Song, Q. and Chissom, B.S., 1993a, Forecasting enrollments with fuzzy time series: Part I, Fuzzy Sets and Systems, 54, p. 1–9.
[18]Song, Q. and Chissom, B.S., 1993b, Fuzzy time series and its models, Fuzzy Sets and Systems, 54, p. 268–277.
[19]Song, Q. and Chissom, B.S., 1994, Forecasting Enrollments With Fuzzy Time Series: Part II, Fuzzy Sets and Systems, 62, p. 1–8.
[20]Chen, S.M. and Hwang, J.R., 1998, Handling forecasting problems using fuzzy time series, Fuzzy Sets Syst., Volume 100, No. 2, p. 217-228.