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Can I read Learning Maximal Structure Rules in Fuzzy Logic for Knowledge Acquisition in Expert Systems on EtoBox?
Learning Maximal Structure Rules in Fuzzy Logic for Knowledge Acquisition in Expert Systems by J.L. Castro; J.J. Castro-Schez; J.M. Zurita is a Computer Science article available to read on EtoBox.
What is Learning Maximal Structure Rules in Fuzzy Logic for Knowledge Acquisition in Expert Systems about?
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.
Who reads Learning Maximal Structure Rules in Fuzzy Logic for Knowledge Acquisition in Expert Systems?
It is typically read by researchers, students, and practitioners in Computer Science.
- Author
- J.L. Castro; J.J. Castro-Schez; J.M. Zurita
- Publisher
- Elsevier Science; Elsevier ; Elsevier BV (ISSN 0165-0114)
- Published
- 1999
- Language
- EN
- Field
- Computer Science (Physical Sciences)
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