Document (#12282)

Author

Quast, D.

Title

Neural fuzzy networks reasoning with uncertainty : what can knowledge- and information retrieval engineers learn from brain research?

Source

Svensk biblioteks forskning. 1995, no.1, S.27-34

Year

1995

Abstract

Describes the theoretical constructs of neural networks and fuzzy logic which have traditionally been treated as 2 distinctly different technologies. However, when neural networks are combined with the mathematical logic of fuzzy set theory new structures and ideas of architectures of knowledge and information retrieval systems can be explored. Concludes that new software and/or hardware for knowledge systems can be developed by using neural networks to define the rules and then using fuzzy logic to run the rules. Combining aspects of fuzzy inference with the flexibility and trainability of artificial neural networks makes it possible to form networks that embed prior knowledge and yet can be trained for more optimal behaviour or to adapt to the changing environment

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