Structure identification and parameter optimization for non-linear fuzzy modeling

T–S fuzzy model identification based on a novel fuzzy c-regression model clustering algorithm

“…1 9 Xu and Lu (1987) 2 0.328 Pedrycz (1984) 2 0.321 Chen et al (1998) 2 0.268 Kroll (1996) 2 0 . 1 4 9 Evsukoff et al (2002) 2 0.090 Kim et al (1997) 6 0.062 Kim et al (1998a) 6 0.055 Chiu (1996) 3 0.072 Tsekouras (2005) 6 0.075 Kung and Su (2007) 2 0.0518 Bagis (2008) 4 0 . 1 4 8 Our model 4 0.0498 Table 5 List of the parameters of our model in the Box and Jenkins example.…”

An extended Takagi–Sugeno–Kang inference system (TSK+) with fuzzy interpolation and its rule base generation

“…In order to evaluate its ability in handling dense data sets, a two-input and single-output nonlinear mathematical model expressed in Eq. 18 was employed as a test bed, given that it has been used by Evsukoff et al (2002) and Rezaee and Zarandi (2010).…”

“…By employing the proposed approach, 14 TSK fuzzy rules in total were generated. To allow a direct comparison, the mean-squares error (MSE) was used as the measurement of models, by following the work presented in Evsukoff et al (2002) and zRezaee and Zarandi (2010). The detailed calculations of this experiment are omitted here.…”

A new T–S fuzzy-modeling approach to identify a boiler–turbine system

“…Number of rules MSE Box and Jenkins (1970) 6 0.202 Tong (1980) 2 0.469 Sugeno and Yasukawa (1993) 3 0.19 Xu and Lu (1987) 2 0.328 Pedrycz (1984) 2 0.321 Chen, Xi, and Zhang (1998) 2 0.268 Kroll (1996) 2 0.149 Evsukoff, Branco, and Galichet (2002) 2 0.090 Kim et al (1997) 6 0.062 6 0.055 Chiu (1996) 3 0.072 Tsekouras (2005) 6 0.075 Bagis (2008) 4 0.148 Our model 3 0.056 for turbine, u 3 is level of feedwater regulator, y 3 is level of drum (m), a cs is coefficient for the quality of steam, a cs ¼ ð1 À 0:001538x 3 Þð0:8x 1 À 25:6Þ x 3 ð1:0394 À 0:0012304x 1 Þ ;…”