کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
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390046 | 661207 | 2010 | 23 صفحه PDF | دانلود رایگان |
A calculus of appropriateness measures of linguistic expressions is proposed, which is based on the prototype theory and random set theory interpretation of vague concepts. A prototype-based rule inference system is then introduced to incorporate linguistic labels in the rule antecedents and linear functions in the consequents of rules. And a rule learning algorithm is developed by combining a new clustering algorithm and a conjugate gradient algorithm. The proposed prototype-based inference system is then applied to a number of benchmark prediction problems including a nonlinear two-dimensional surface, the Mackey–Glass time series and the sunspot time-series. Results suggest that the proposed model is very robust and can perform well in high-dimensional noisy data.
Journal: Fuzzy Sets and Systems - Volume 161, Issue 21, 1 November 2010, Pages 2831-2853