Ponencia
XFSL: A tool for supervised learning of fuzzy systems
Autor/es | Moreno Velo, Francisco José
Baturone Castillo, María Iluminada Sánchez Solano, Santiago Barriga Barros, Ángel |
Departamento | Universidad de Sevilla. Departamento de Electrónica y Electromagnetismo |
Fecha de publicación | 2001 |
Fecha de depósito | 2017-03-28 |
Publicado en |
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Resumen | This paper presents Xfsl, a tool for the automatic tuning of fuzzy systems using supervised learning algorithms. The tool provides a wide set of learning algorithms, which can be used to tune complex systems. An important ... This paper presents Xfsl, a tool for the automatic tuning of fuzzy systems using supervised learning algorithms. The tool provides a wide set of learning algorithms, which can be used to tune complex systems. An important issue is that Xfsl is integrated into the fuzzy system development environment Xfuzzy 3.0, and hence, it can be easily employed within the design flow of a fuzzy system. |
Agencias financiadoras | Comisión Interministerial de Ciencia y Tecnología (CICYT). España European Commission (EC). Fondo Europeo de Desarrollo Regional (FEDER) |
Identificador del proyecto | TIC98-0869
1FD97-0956-C3-02 |
Cita | Moreno Velo, F.J., Baturone Castillo, M.I., Sánchez Solano, S. y Barriga Barros, Á. (2001). XFSL: A tool for supervised learning of fuzzy systems. En European Symposium on Intelligent Technologies, Hybrid Systems and their implementation on Smart Adaptive Systems (EUNITE-2001), Tenerife. |