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A Particle Swarm Intelligence based Fuzzy Time Series Forecasting Model

by Jilani T. A., Burney S.M.A., Amjad U., Tanveer A. Siddiqui
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 38 - Number 10
Year of Publication: 2012
Authors: Jilani T. A., Burney S.M.A., Amjad U., Tanveer A. Siddiqui
10.5120/4742-6776

Jilani T. A., Burney S.M.A., Amjad U., Tanveer A. Siddiqui . A Particle Swarm Intelligence based Fuzzy Time Series Forecasting Model. International Journal of Computer Applications. 38, 10 ( January 2012), 47-52. DOI=10.5120/4742-6776

@article{ 10.5120/4742-6776,
author = { Jilani T. A., Burney S.M.A., Amjad U., Tanveer A. Siddiqui },
title = { A Particle Swarm Intelligence based Fuzzy Time Series Forecasting Model },
journal = { International Journal of Computer Applications },
issue_date = { January 2012 },
volume = { 38 },
number = { 10 },
month = { January },
year = { 2012 },
issn = { 0975-8887 },
pages = { 47-52 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume38/number10/4742-6776/ },
doi = { 10.5120/4742-6776 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:25:10.477215+05:30
%A Jilani T. A.
%A Burney S.M.A.
%A Amjad U.
%A Tanveer A. Siddiqui
%T A Particle Swarm Intelligence based Fuzzy Time Series Forecasting Model
%J International Journal of Computer Applications
%@ 0975-8887
%V 38
%N 10
%P 47-52
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this paper, we have presented a new particle swarm optimization based multivariate fuzzy time series forecasting method. This method assumes five-factors with one main factor of interest. History of past three years is used for making new forecasts. This new method is applied in forecasting total number of car accidents in Belgium using four secondary factors. We also make comparison of our proposed method with existing methods of fuzzy time series forecasting. Experimentally, it is proved that our proposed method perform better than many existing fuzzy time series forecasting methods. The interest of this paper centers in applying swarm intelligence approaches in forecasting related problems. The dataset is taken from National Institute of Statistics, Belgium.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Average forecasting error rate (AFER) Fuzziness of fuzzy sets Fuzzy If-Then rule particle swarm optimization (PSO)

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