TY - GEN
T1 - A new TSK fuzzy modeling approach
AU - Kim, Kyoungjung
AU - Kim, You Keun
AU - Kim, Euntai
AU - Park, Mignon
PY - 2004
Y1 - 2004
N2 - In this paper, a new robust TSK fuzzy modeling algorithm is proposed. The proposed algorithm is the modified version of noise clustering algorithm. Various robust approaches to deal with the data containing noise or outliers in real applications were proposed, but most algorithms process clustering of data first and then conduct fuzzy regression. We propose the algorithm that parameters of the premise part and the consequent part are obtained simultaneously. The proposed algorithm shows good performance against noise or outliers. Without adaptation of parameters, the proposed algorithm shows the superior performance over other approaches.
AB - In this paper, a new robust TSK fuzzy modeling algorithm is proposed. The proposed algorithm is the modified version of noise clustering algorithm. Various robust approaches to deal with the data containing noise or outliers in real applications were proposed, but most algorithms process clustering of data first and then conduct fuzzy regression. We propose the algorithm that parameters of the premise part and the consequent part are obtained simultaneously. The proposed algorithm shows good performance against noise or outliers. Without adaptation of parameters, the proposed algorithm shows the superior performance over other approaches.
UR - http://www.scopus.com/inward/record.url?scp=11144284637&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=11144284637&partnerID=8YFLogxK
U2 - 10.1109/FUZZY.2004.1375498
DO - 10.1109/FUZZY.2004.1375498
M3 - Conference contribution
AN - SCOPUS:11144284637
SN - 0780383532
T3 - IEEE International Conference on Fuzzy Systems
SP - 773
EP - 776
BT - 2004 IEEE International Conference on Fuzzy Systems - Proceedings
T2 - 2004 IEEE International Conference on Fuzzy Systems - Proceedings
Y2 - 25 July 2004 through 29 July 2004
ER -