چکیده مقاله
Type 2 fuzzy systems have three dimensional membership functions and a footprint of uncertainties Hence, they could handle higher levels of uncertainties in comparison with type 1 fuzzy systems Here, we employ interval type 2 Takagi Sugeno Kang TSK fuzzy systems for system identification and time series prediction The designed type 2 fuzzy system uses direct defuzzification which avoids the computationally extensive calculations of the Karnik Mendel algorithm A type 1 fuzzy system is also designed in the same way for comparative purposes The weights of the fuzzy systems are updated using the gradient descent algorithm The performance of the two fuzzy systems is evaluated in chaotic time series prediction Simulation results show that the type 2 fuzzy system reaches lower error for different levels of measurement noise
کلیدواژهها
نویسندگان
F Baghbani
Department of Electrical and Computer Engineering, Semnan University, Semnan, Iran
Mehraneh Hemmati
Department of Electrical and Computer Engineering, Semnan University, Semnan, Iran
شیوه ارجاع
Baghbani, F and Hemmati, Mehraneh,1400,Design of an Interval Type-2 TSK Fuzzy System for System Identification with Application to Time-Series Prediction,Fourth International Conference on Soft Computing
ارائهشده در
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