TY  - CONF
A1  - Hasan, M.H.
A1  - Jaafar, J.
A1  - Hassan, M.F.
N2  - Existing works investigated the construction of fuzzy type-1 (FT1) membership function (MF). However, recent findings show that interval type-2 (IT2)-based fuzzy inference system (FIS) is found to be more accurate and precise than FT1. Hence, the research on how to generate IT2 MF from data is significant to be conducted. Besides, existing works also investigated the construction of IT2 MF using IT2 Fuzzy C-Means (FCM) method. The evident shows that the construction of IT2 MF from IT2 FCM method may not suitable for all kind of data sets. Hence, the objectives of this paper are to present a methodology for the generation of IT2 MF using general FCM (non-IT2 FCM) data clustering method and to describe the implementation of the proposed IT2 MFs in an FIS. The experiment results show that IT2 MFs have successfully been constructed by using general FCM and two clusters' centers approach. © 2016 IEEE.
Y1  - 2016///
N1  - cited By 7; Conference of 3rd International Conference on Computer and Information Sciences, ICCOINS 2016 ; Conference Date: 15 August 2016 Through 17 August 2016; Conference Code:125433
EP  - 632
SP  - 627
TI  - Fuzzy C-Means and two clusters' centers method for generating interval type-2 membership function
SN  - 9781509051342
PB  - Institute of Electrical and Electronics Engineers Inc.
UR  - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85010424299&doi=10.1109%2fICCOINS.2016.7783288&partnerID=40&md5=2cf06efa6569d764d0f561ec6e2ed1d0
ID  - scholars6483
KW  - Cluster analysis; Clustering algorithms; Fuzzy inference; Fuzzy systems; Information science
KW  -  Data clustering; Data clustering methods; Fuzzy C mean; Fuzzy inference systems
KW  -  Membership functions
AV  - none
ER  -