This paper presents an approach to design conceptual knowledge acquisition. The approach was basically developed for knowledge acquisition in BRZDY1, a learning expert system for conceptual design currently under development. A formal identification of qualitative, conceptual design decisions, based
โฆ LIBER โฆ
Learning maximal structure rules in fuzzy logic for knowledge acquisition in expert systems
โ Scribed by J.L. Castro; J.J. Castro-Schez; J.M. Zurita
- Publisher
- Elsevier Science
- Year
- 1999
- Tongue
- English
- Weight
- 736 KB
- Volume
- 101
- Category
- Article
- ISSN
- 0165-0114
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โฆ Synopsis
The aim of this article is to present a new approach to machine learning (precisely in classification problems) in which the use of fuzzy logic has been taken into account. We intend to show that fiazzy logic introduces new elements in the identification process, mainly due to the facility to manage imprecise information. An inductive algorithm generating a set of fuzzy rules identifying the system will be achieved. The maximal structure of a fuzzy rule will be found using this algorithm.
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