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- W1552250343 abstract "In this paper, we suggest a utility learning algorithm for tuning fuzzy rules by using input-output training data, based on the gradient descent method. The major advantage of this method is that the fuzzy rules or membership functions can be learned without changing the form of the fuzzy rule table used in usual fuzzy controls, so that the case of weak-firing can be avoided, which is different from the conventional learning algorithm. Furthermore, we illustrated the efficiency of the suggested learning algorithm by means of several numerical examples." @default.
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- W1552250343 date "2002-12-24" @default.
- W1552250343 modified "2023-09-26" @default.
- W1552250343 title "A learning algorithm for tuning fuzzy rules based on the gradient descent method" @default.
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- W1552250343 doi "https://doi.org/10.1109/fuzzy.1996.551719" @default.
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