This paper presents a new method for designing adaptive neuro-fuzzy inference systems (ANFIS). Improvements are made by introducing specially developed orthogonal functions into the very structure of ANFIS, specifically, into the layer that imitates Sugeno stile defuzzification. These functions are specially tailored for analysis and synthesis of dynamic systems and they also contain an adaptive measure of the variability of the systems operating in a real environment, which can be implemented inside the ANFIS as hormonal effect.
Modeling of Dynamic Systems Using Orthogonal Endocrine Adaptive Neuro-Fuzzy Inference Systems
Contributed by the Dynamic Systems Division of ASME for publication in the JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT, AND CONTROL. Manuscript received March 9, 2015; final manuscript received May 29, 2015; published online July 10, 2015. Assoc. Editor: Dumitru I. Caruntu.
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Milojković, M., Antić, D., Milovanović, M., Nikolić, S. S., Perić, S., and Almawlawe, M. (July 10, 2015). "Modeling of Dynamic Systems Using Orthogonal Endocrine Adaptive Neuro-Fuzzy Inference Systems." ASME. J. Dyn. Sys., Meas., Control. September 2015; 137(9): 091013. https://doi.org/10.1115/1.4030758
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