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Reseach Article

A Two Phase Algorithm for Fuzzy Time Series Forecasting using Genetic Algorithm and Particle Swarm Optimization Techniques

by Usman Amjad, Tahseen A. Jilani, Farah Yasmeen
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 55 - Number 16
Year of Publication: 2012
Authors: Usman Amjad, Tahseen A. Jilani, Farah Yasmeen
10.5120/8842-3129

Usman Amjad, Tahseen A. Jilani, Farah Yasmeen . A Two Phase Algorithm for Fuzzy Time Series Forecasting using Genetic Algorithm and Particle Swarm Optimization Techniques. International Journal of Computer Applications. 55, 16 ( October 2012), 34-40. DOI=10.5120/8842-3129

@article{ 10.5120/8842-3129,
author = { Usman Amjad, Tahseen A. Jilani, Farah Yasmeen },
title = { A Two Phase Algorithm for Fuzzy Time Series Forecasting using Genetic Algorithm and Particle Swarm Optimization Techniques },
journal = { International Journal of Computer Applications },
issue_date = { October 2012 },
volume = { 55 },
number = { 16 },
month = { October },
year = { 2012 },
issn = { 0975-8887 },
pages = { 34-40 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume55/number16/8842-3129/ },
doi = { 10.5120/8842-3129 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:57:27.451752+05:30
%A Usman Amjad
%A Tahseen A. Jilani
%A Farah Yasmeen
%T A Two Phase Algorithm for Fuzzy Time Series Forecasting using Genetic Algorithm and Particle Swarm Optimization Techniques
%J International Journal of Computer Applications
%@ 0975-8887
%V 55
%N 16
%P 34-40
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Fuzzy Time series is being used for forecasting since last two decades for forecasting. Nature inspired computing techniques like other domains are now being used for optimization purpose in Fuzzy Time Series forecasting models to get improved results. In this paper we have presented a new algorithm for multivariate fuzzy time series forecasting having two phases. Genetic Algorithm and Particle Swarm Optimization techniques are used in this algorithm for optimization. We applied our algorithm on Taiwan forex Exchange (TAIFEX) index and got better results and minimized error rate as compared to previous methods.

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Index Terms

Computer Science
Information Sciences

Keywords

Fuzzy time series two-factor high-order fuzzy logical relationships Genetic Algorithm Particle Swarm Optimization TAIFEX index