Interpolative Fuzzy Inferences Using Least Square Principle Armin
نویسنده
چکیده
Many researchers have been interested in approximation properties of fuzzy logic systems (FLS), which like neural networks can be seen as approximation schemes. Almost all of them tackled Mamdani fuzzy model, which was shown to have many interesting features. This paper aims to present alternatives for traditional inference mechanisms and CRI method. The most attractive advantage of these new methods are their higher robustness with respect to changes in rule base and ability to operate when latter is sparse. In this paper, interpolations with two type of high order polynomials and ß-function is reported. Keywords—ß-function, Fuzzy interpolation, fuzzy inference engine, fuzzy curve fitting, least square
منابع مشابه
Interpolative Fuzzy Inferences Using Least Square Principle
Many researchers have been interested in approximation properties of fuzzy logic systems (FLS), which like neural networks can be seen as approximation schemes. Almost all of them tackled Mamdani fuzzy model, which was shown to have many interesting features. This paper aims to present alternatives for traditional inference mechanisms and CRI method. The most attractive advantage of these new m...
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