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IJAR
2006
133views more  IJAR 2006»
13 years 4 months ago
Extraction of similarity based fuzzy rules from artificial neural networks
A method to extract a fuzzy rule based system from a trained artificial neural network for classification is presented. The fuzzy system obtained is equivalent to the correspondin...
Carlos Javier Mantas, José Manuel Puche, J....
AIIA
2001
Springer
13 years 9 months ago
A Knowledge-Based Neurocomputing Approach to Extract Refined Linguistic Rules from Data
– This paper proposes a knowledge-based neurocomputing approach to extract and refine a set of linguistic rules from data. A neural network is designed along with its learning al...
Giovanna Castellano, Anna Maria Fanelli
ENVSOFT
2008
115views more  ENVSOFT 2008»
13 years 4 months ago
Adaptive fuzzy modeling versus artificial neural networks
In this paper two areas of soft computing (fuzzy modeling and artificial neural networks) are discussed. Based on the fundamental mathematical similarity of fuzzy technique and ra...
Ralf Wieland, Wilfried Mirschel
CORR
2010
Springer
150views Education» more  CORR 2010»
13 years 4 months ago
Extraction of Symbolic Rules from Artificial Neural Networks
Although backpropagation ANNs generally predict better than decision trees do for pattern classification problems, they are often regarded as black boxes, i.e., their predictions c...
S. M. Kamruzzaman, Md. Monirul Islam
ESANN
2003
13 years 6 months ago
Extraction of fuzzy rules from trained neural network using evolutionary algorithm
This paper presents our approach to the rule extraction problem from trained neural network. A method called REX is briefly described. REX acquires a set of fuzzy rules using an ev...
Urszula Markowska-Kaczmar, Wojciech Trelak