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
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;
Conference_Titel :
Information Fusion, 2000. FUSION 2000. Proceedings of the Third International Conference on
Conference_Location :
Paris, France
Print_ISBN :
2-7257-0000-0
DOI :
10.1109/IFIC.2000.862460
