Estimating the Nonparametric Regression Function of the Fuzzy Phenomena by using Simulink
الكلمات المفتاحية:
Fuzzy data, fuzzy nonparametric regression model, local linear smooth, kernel smooth, fuzzy Nadarya-Watson.الملخص
Statistical data is sometimes obtained from uncertain resources or fuzzy phenomenon therefore the conventional statistical analysis becomes unable to interpret the result of these data. And addition it is difficult to find function form or probability distribution for this kind of data So, must be using appropriate analysis model achieved assumption fuzzy data or phenomenon.
Concern has been focused on utilizing the fuzzy nonparametric regression models, which are convenient to deal with this data, in this paper presents a compare between to smoothing approaches to estimating the fuzzy nonparametric regression function by using crisp independent and fuzzy dependent variables within uncertain phenomena. A triangular membership function was adopted to generate the belonging of the elements within the fuzzy set. where applied the local linear smoothing and kernel smoothing, suggested two test functions were proposed to show the applied methods’ The results of MATLAB simulations and the applied criteria of differentiating have shown the superiority of the local linear smoothing over kernel smoothing for the two proposed test functions. So we goal to modeling the fuzziness phenomena
التنزيلات
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التنزيلات
منشور
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2023-04-14
