DocumentCode
3026907
Title
Automatic variable selection and granular adaptation in fuzzy Boolean nets
Author
Tomé, José A B
Author_Institution
Inst. Superior Tecnico, Lisbon, Portugal
fYear
1999
fDate
36342
Firstpage
620
Lastpage
624
Abstract
In this work the problem of meta-learning, that is, perceiving what to learn (which variables, which granularity), is addressed in the context of Boolean nets with fuzzy behaviour. Fuzzy relational operators, embedded in those neural networks, are defined and the author shows how they can be used to establish the relevant antecedents as well as their topology of the network according these concepts and in order to efficiently learn a given set of rules from experiments is presented
Keywords
Boolean algebra; fuzzy neural nets; fuzzy systems; unsupervised learning; automatic variable selection; fuzzy Boolean nets; fuzzy relational operators; granular adaptation; meta-learning; network topology; rule learning; Fires; Fuzzy neural networks; Fuzzy reasoning; Fuzzy systems; Input variables; Intelligent networks; Neural networks; Neurons; Noise level; Tiles;
fLanguage
English
Publisher
ieee
Conference_Titel
Fuzzy Information Processing Society, 1999. NAFIPS. 18th International Conference of the North American
Conference_Location
New York, NY
Print_ISBN
0-7803-5211-4
Type
conf
DOI
10.1109/NAFIPS.1999.781768
Filename
781768
Link To Document