Advances in Time Series Forecasting

Volume: 1

Indexed in: Scopus, EBSCO, Ulrich's Periodicals Directory

Time series analysis is applicable in a variety of disciplines, such as business administration, economics, public finance, engineering, statistics, econometrics, mathematics and actuarial sciences. ...
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A New Method for Forecasting Fuzzy Time Series with Triangular Fuzzy Number Observations

Pp. 48-55 (8)

Erol Eǧrioǧlu, Cagdas Hakan Aladag and Ufuk Yolcu

Abstract

Most of the time series faced in real life are fuzzy time series and these time series have to be forecasted by fuzzy time series forecasting methods. Therefore, there have been many studies in the literature in which various fuzzy time series approaches are proposed. The fuzzy time series methods introduced in the literature have been generally proposed to analyze fuzzy time series whose observations are fuzzy sets. On the other hand, Song et al. firstly improved a fuzzy time series model to analyze fuzzy time series whose observations are triangular fuzzy numbers [1]. Their method requires complex arithmetic operations for triangular fuzzy numbers. We propose a novel fuzzy time series forecasting approach based on simulation and feed forward neural networks to forecast fuzzy time series including triangular fuzzy numbers. The proposed method is applied to gold prices in Turkey series to show the applicability of the method.

Keywords:

Artificial neural networks, Fuzzy time series, Forecasting, Gold prices in Turkey, Triangular fuzzy number.

Affiliation:

Ondokuz Mayis University, Faculty of Arts and Science, Department of Statistics, 55139, Samsun, Turkey