An accurate comparison of type-reduction algorithms for interval type-2 fuzzy sets using simulated data
Haihua Xing, Hongyan Lin, Chunhui Song
Available Online March 2017.
- https://doi.org/10.2991/ifmca-16.2017.63How to use a DOI?
- 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)
- 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.
- 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 -