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Abstract:

Although linguistic models are highly descriptive, they suffer from inaccuracy in some complex problems. This fact is due to problems related to the inflexibility of the linguistic rule structure that has been considered. Moreover, methods often employed to design these models from data are also biased by the former structure and by their nature, which is close to prototype identification algorithms. In order to deal with these problems of linguistic modeling, an extension of the knowledge base of linguistic fuzzy rule-based systems was previously introduced, i.e., the hierarchical knowledge base (HKB) (IEEE Trans. Fuzzy Systems 10 (1) (2002) 2). Hierarchical linguistic fuzzy models, derived from this structure, are viewed as a class of local modeling approaches. They attempt to solve a complex modeling problem by decomposing it into a number of simpler linguistically interpretable subproblems. From this perspective, linguistic modeling using an HKB can be regarded as a search for a decomposition of a non-linear system that gives a desired balance between the interpretability and the accuracy of the model. Using this approach, we are able to effectively explore the fact that the complexity of the systems is usually not uniform. We propose a well-defined hierarchical environment adopting a more general treatment than the typical prototype-oriented learning methods. This iterative hierarchical methodology takes the HKB as a base and performs a wide variety of linguistic modeling. More specifically, from fully interpretable to fully accurate, as well as intermediate trade-offs, hierarchical linguistic models. With the aim of analyzing the behavior of the proposed methodology, two real-world electrical engineering distribution problems from Spain have been selected. Successful results were obtained in comparison with other system modeling techniques. © 2002 Elsevier B.V. All rights reserved.

Registro:

Documento: Artículo
Título:A hierarchical knowledge-based environment for linguistic modeling: Models and iterative methodology
Autor:Cordón, O.; Herrera, F.; Zwir, I.
Filiación:Department of Computer Science, E.T.S. de Ing. Informática, University of Granada, 18071 Granada, Spain
Department of Computer Science, F.C.E. y N., University of Buenos Aires, 1428 Buenos Aires, Argentina
Palabras clave:Fuzzy rule-based systems; Genetic algorithms; Hierarchical knowledge base; Hierarchical linguistic partitions; Linguistic modeling; Rule selection; Genetic algorithms; Iterative methods; Linguistics; Problem solving; Rule selection; Fuzzy sets
Año:2003
Volumen:138
Número:2
Página de inicio:307
Página de fin:341
DOI: http://dx.doi.org/10.1016/S0165-0114(02)00388-3
Título revista:Fuzzy Sets and Systems
Título revista abreviado:Fuzzy Sets Syst
ISSN:01650114
CODEN:FSSYD
Registro:https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_01650114_v138_n2_p307_Cordon

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Citas:

---------- APA ----------
Cordón, O., Herrera, F. & Zwir, I. (2003) . A hierarchical knowledge-based environment for linguistic modeling: Models and iterative methodology. Fuzzy Sets and Systems, 138(2), 307-341.
http://dx.doi.org/10.1016/S0165-0114(02)00388-3
---------- CHICAGO ----------
Cordón, O., Herrera, F., Zwir, I. "A hierarchical knowledge-based environment for linguistic modeling: Models and iterative methodology" . Fuzzy Sets and Systems 138, no. 2 (2003) : 307-341.
http://dx.doi.org/10.1016/S0165-0114(02)00388-3
---------- MLA ----------
Cordón, O., Herrera, F., Zwir, I. "A hierarchical knowledge-based environment for linguistic modeling: Models and iterative methodology" . Fuzzy Sets and Systems, vol. 138, no. 2, 2003, pp. 307-341.
http://dx.doi.org/10.1016/S0165-0114(02)00388-3
---------- VANCOUVER ----------
Cordón, O., Herrera, F., Zwir, I. A hierarchical knowledge-based environment for linguistic modeling: Models and iterative methodology. Fuzzy Sets Syst. 2003;138(2):307-341.
http://dx.doi.org/10.1016/S0165-0114(02)00388-3