In this paper we sketch a method to design expert systems, probabilistic in nature, by the notions of Fuzzy Formal Context and Fuzzy Similarity. Two cases are considered “similar” if they satisfy the same observable properties. The expert system should give the probability that a new examined case satisfies a non observable property. We admit the presence of eventually vague properties and we need an adequate definition of probability of fuzzy events.
Fuzzy Formal Context, Similarity and Probabilistic Expert System / Coppola, C.; Gerla, G.; Pacelli, T.. - (2006). (Intervento presentato al convegno International Symposium on Fuzzy and Rough Sets (ISFUROS 2006) tenutosi a Santa Clara, Cuba nel 5- 8 Dicembre, 2006).
Fuzzy Formal Context, Similarity and Probabilistic Expert System
Pacelli T.
2006
Abstract
In this paper we sketch a method to design expert systems, probabilistic in nature, by the notions of Fuzzy Formal Context and Fuzzy Similarity. Two cases are considered “similar” if they satisfy the same observable properties. The expert system should give the probability that a new examined case satisfies a non observable property. We admit the presence of eventually vague properties and we need an adequate definition of probability of fuzzy events.File | Dimensione | Formato | |
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Fuzzy Formal Context, Similarity and Probabilistic Expert Systems_Coppola,Gerla,Pacelli.pdf
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