A Novel Dual Factor Fuzzy Time Series Forecasting based on new Fuzzy sets and Interval Definition by Evolution Strategies

Authors

M.H. Fazel Zarandi, Polytechnic of IranFollow
A. Molladavoudi, Department of Industrial Engineering, Amirkabir University of technology (Polytechnic)Follow
H. Davari Ardakani, Department of Industrial Engineering, Amirkabir University of technology (Polytechnic)Follow
I. Burhan Turksen, TOBB Economics and Technology UniversityFollow

Track

Research-in-Progress

Abstract

This paper proposes a new dual factor time-invariant fuzzy time series method that is capable of forecasting stock marketPrice Index. The proposed approach uses a new fuzzy logic relationship definition. According to the utilized membershipdegrees used to define the fuzzy relationships, each datum may belong to two distinct intervals rather than only one interval.This assumption, which has not been considered in the other studies, contributes to better forecasting results. In addition, anappropriate meta-heuristic algorithm for continuous solution schemes, namely evolution strategies (ES), is utilized to identifythe appropriate interval lengths. The proposed approach has been tested on TAIFEX index. The computational results showedthat the proposed approach outperforms the former studies.

Recommended Citation

Zarandi, M.H. Fazel; Molladavoudi, A.; Ardakani, H. Davari; and Turksen, I. Burhan, "A Novel Dual Factor Fuzzy Time Series Forecasting based on new Fuzzy sets and Interval Definition by Evolution Strategies" (2011). AMCIS 2011 Proceedings - All Submissions. 15.
https://aisel.aisnet.org/amcis2011_submissions/15