Improving simple linguistic fuzzy models by means of the weighted COR methodology

Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)

Volumn 2527, Issue , 2002, Pages 294-302

  Alcalá, Rafael ^a   Casillas, Jorge ^b   Cordón, Oscar ^b   Herrera, Francisco ^b  

^a UNIVERSITY OF JAÉN   (Spain)

^b UNIVERSITY OF GRANADA   (Spain)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; COMPUTATIONAL LINGUISTICS;

INTERPRETABILITY; LINGUISTIC FUZZY MODELS; SYSTEM ACCURACY;

LINGUISTICS;

EID: 34547245231     PISSN: 03029743     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1007/3-540-36131-6_30     Document Type: Conference Paper

References (11)

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2. Casillas, J., Cordón, O., Herrera, F.: COR: A methodology to improve ad hoc datadriven linguistic rule learning methods by inducing cooperation among rules. IEEE Transactions on Systems, Man, andCyb ernetics-Part B: Cybernetics (2002). To appear
3. Casillas, J., Cordón, O., Herrera, F.: Different approaches to induce cooperation in fuzzy linguistic models under the COR methodology. In: Bouchon-Meunier, B., Gutiérrez-Ríos, J., Magdalena, L., Yager, R.R. (Eds.): Techniques for Constructing Intelligent Systems. Springer-Verlag, Heidelberg, Germany (2002)
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