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This paper presents a fuzzy-neural network that admits both numeric as well as linguistic inputs. Numeric inputs are fuzzified by input nodes upon presentation to the network. Fuzzy rule-based knowledge is translated directly into a network architecture. Connections in the network are represented by fuzzy sets: Input to hidden connections represent rule antecedents; hidden to output connections represent...
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