DocumentCode
353783
Title
A symbolic neuro-fuzzy collaborative approach for inducing knowledge in a pharmacological domain
Author
Nicoletti, M. Carmo ; Ramer, Arthur ; Nicoletti, M. Aparecida
Author_Institution
Sch. of Comput. Sci. & Eng., New South Wales Univ., Kensington, NSW, Australia
Volume
1
fYear
2000
fDate
10-13 July 2000
Abstract
This paper discusses the experiments conducted with two conceptually different machine learning systems in a pharmacological domain related to the use of different excipients in drug production. It shows how a symbolic system can be used, in a collaborative way, to help a neuro-fuzzy system to induce a more appropriate set of fuzzy rules.
Keywords
cooperative systems; fuzzy neural nets; learning by example; pharmaceutical industry; sensor fusion; symbol manipulation; drug production; excipients; fuzzy classification; fuzzy rules induction; hybrid systems; knowledge induction; machine learning systems; pharmacological domain; symbolic neuro-fuzzy collaborative approach; Australia; Collaboration; Drugs; Fuzzy neural networks; Fuzzy sets; Fuzzy systems; Knowledge engineering; Learning systems; Neural networks; Production systems;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Fusion, 2000. FUSION 2000. Proceedings of the Third International Conference on
Conference_Location
Paris, France
Print_ISBN
2-7257-0000-0
Type
conf
DOI
10.1109/IFIC.2000.862460
Filename
862460
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