eprintid: 6482
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/00/64/82
datestamp: 2023-11-09 16:18:16
lastmod: 2023-11-09 16:18:16
status_changed: 2023-11-09 16:06:51
type: conference_item
metadata_visibility: show
creators_name: Hassan, S.
creators_name: Jaafar, J.
creators_name: Khanesar, M.A.
creators_name: Khosravi, A.
title: Artificial bee colony optimization of interval type-2 fuzzy extreme learning system for chaotic data
ispublished: pub
keywords: Computer circuits; Forecasting; Fuzzy logic; Information science; Knowledge acquisition; Learning systems; Optimization, Artificial bee colony optimizations; Data set; Extreme learning machine; Forecasting performance; Hybrid learning algorithm; Interval type-2 fuzzy; Interval type-2 fuzzy logic systems; Optimal parameter, Learning algorithms
note: cited By 3; Conference of 3rd International Conference on Computer and Information Sciences, ICCOINS 2016 ; Conference Date: 15 August 2016 Through 17 August 2016; Conference Code:125433
abstract: The major challenge in the design of Interval type-2 fuzzy logic system (IT2FLS) is to determine the optimal parameters for their antecedent and consequent parts. This paper propose a novel hybrid learning algorithm for the design of IT2FLS. The proposed hybrid learning algorithm utilizes the combination of extreme learning machine (ELM) and artificial bee colony optimization (ABC) to tune the parameters of the consequent and antecedent parts of the IT2FLS, respectively. The effective forecasting performance of the proposed hybrid learning algorithm is analyzed by modeling a chaotic data set. It is found that the forecasted errors gradually decrease with decrease in the level of noise in data and vise versa. © 2016 IEEE.
date: 2016
publisher: Institute of Electrical and Electronics Engineers Inc.
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85010426205&doi=10.1109%2fICCOINS.2016.7783237&partnerID=40&md5=4b6f671147a8d732e6a7748feb7a7432
id_number: 10.1109/ICCOINS.2016.7783237
full_text_status: none
publication: 2016 3rd International Conference on Computer and Information Sciences, ICCOINS 2016 - Proceedings
pagerange: 334-339
refereed: TRUE
isbn: 9781509051342
citation:   Hassan, S. and Jaafar, J. and Khanesar, M.A. and Khosravi, A.  (2016) Artificial bee colony optimization of interval type-2 fuzzy extreme learning system for chaotic data.  In: UNSPECIFIED.