Proceedings of the 2016 International Forum on Mechanical, Control and Automation (IFMCA 2016)

An accurate comparison of type-reduction algorithms for interval type-2 fuzzy sets using simulated data

Authors
Haihua Xing, Hongyan Lin, Chunhui Song
Corresponding Author
Haihua Xing
Available Online March 2017.
DOI
https://doi.org/10.2991/ifmca-16.2017.63How to use a DOI?
Keywords
Interval type-2 fuzzy sets(IT2FSs), Type-reduction; Karnik–Mendel (KM) algorithms, Enhanced Karnik–Mendel (EKM) algorithms, Iterative Algorithm with Stop Condition (IASC), Enhanced Iterative Algorithm with Stop Condition(EIASC)
Abstract
In order to find the best type-reduction algorithm of interval type-2 fuzzy sets with different characteristics, this paper makes a comparative analysis of KM, EKM, IASC and EIASC. Experiments are carried out on three type-2 fuzzy sets to compare the four algorithms.The results show that the four algorithms can accurately find the switching points, and the EIASC algorithm is the most efficient. This study provides an accurate and reliable comparative analysis for evaluating the applicability of the algorithm on different data characteristics.
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This is an open access article distributed under the CC BY-NC license.

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Volume Title
Proceedings of the 2016 International Forum on Mechanical, Control and Automation (IFMCA 2016)
Series
Advances in Engineering Research
Publication Date
March 2017
ISBN
978-94-6252-307-4
ISSN
2352-5401
DOI
https://doi.org/10.2991/ifmca-16.2017.63How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Haihua Xing
AU  - Hongyan Lin
AU  - Chunhui Song
PY  - 2017/03
DA  - 2017/03
TI  - An accurate comparison of type-reduction algorithms for interval type-2 fuzzy sets using simulated data
BT  - Proceedings of the 2016 International Forum on Mechanical, Control and Automation (IFMCA 2016)
PB  - Atlantis Press
SP  - 408
EP  - 415
SN  - 2352-5401
UR  - https://doi.org/10.2991/ifmca-16.2017.63
DO  - https://doi.org/10.2991/ifmca-16.2017.63
ID  - Xing2017/03
ER  -