Estimation of Probability Parameters in Probabilistic Fuzzy Systems
محل انتشار: دوازهمین کنفرانس دانشجویی مهندسی برق ایران
سال انتشار: 1388
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 2,070
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شناسه ملی سند علمی:
ISCEE12_182
تاریخ نمایه سازی: 29 اسفند 1387
چکیده مقاله:
The rule base of a Probabilistic Fuzzy System (PFS) consists of fuzzy rules that have multiple consequent parts. Each consequent has an associated probability parameter. This paper is concerned with the estimation of the probability parameters in a PFS. It is assumed in this paper that both the antecedent and the consequent membership functions (mfs) have already been determined and need not be further optimized. In this paper, we show that the conditional probability method generally does not give optimal results in terms of the approximation accuracy of a PFS. As an alternative, we propose to use the maximum likelihood (ML) criterion for estimating the probability parameters in a PFS.
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نویسندگان
Ali Kh. Salehani
Msc. Student on Control Engineering Malek-e-Ashtar University of Technology-Tehran