Academic Journals Database
Disseminating quality controlled scientific knowledge

A NEW FUZZY TIME SERIES ANALYSIS APPROACH BY USING DIFFERENTIAL EVOLUTION ALGORITHM AND CHRONOLOGICALLY-DETERMINED WEIGHTS

ADD TO MY LIST
 
Author(s): Vedide Rezan USLU | Eren BAS | Ufuk YOLCU | Erol EGRIOGLU

Journal: Journal of Social and Economic Statistics
ISSN 2285-388X

Volume: 2;
Issue: 1;
Start page: 18;
Date: 2013;
VIEW PDF   PDF DOWNLOAD PDF   Download PDF Original page

Keywords: Fuzzy time series | Fuzzification | Differential evolution algorithm | Forecasting

ABSTRACT
Fuzzy time series approaches, which do not require the strict assumptions of traditional time series approaches, generally consist of three stages. These stages are called as the fuzzification of crisp time series observations, the identification of fuzzy relationships and the defuzzification, respectively. All of these stages play an important role on the forecasting performance of the model. By this study we want to contribute to the stage of fuzzification so that the interval length is determined by using the differential evolution algorithm and also we take into account chronological-determined weights in the stage of defuzzification.

Tango Jona
Tangokurs Rapperswil-Jona

     Save time & money - Smart Internet Solutions