| dc.creator | Apolloni, Javier | |
| dc.creator | Kavka, Carlos | |
| dc.creator | Roggero, Patricia | |
| dc.date | 2005-05 | |
| dc.date | 2005 | |
| dc.date | 2012-09-19T12:21:58Z | |
| dc.identifier | http://sedici.unlp.edu.ar/handle/10915/21160 | |
| dc.identifier | isbn:950-665-337-2 | |
| dc.description | A fuzzy controller is usually designed by formulating the knowledge of a human expert into a set of linguistic variables and fuzzy rules. As it is well known, the use of prior knowledge can dramatically improve the performance and quality of the fuzzy system design process. In previous works we have introduced the RFV model, a representation for recurrent fuzzy controllers based on Voronoi diagrams that can represent fuzzy systems with synergistic rules, ful lling the completeness property and providing a simple way to introduce prior knowledge. In this work we present our current approach in the study of the inclusion of prior knowledge in the context of the RFV model. | |
| dc.description | Eje: Inteligencia artificial | |
| dc.description | Red de Universidades con Carreras en Informática (RedUNCI) | |
| dc.format | application/pdf | |
| dc.format | 349-356 | |
| dc.language | en | |
| dc.relation | VII Workshop de Investigadores en Ciencias de la Computación | |
| dc.rights | http://creativecommons.org/licenses/by-nc-sa/2.5/ar/ | |
| dc.rights | Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5) | |
| dc.subject | Ciencias Informáticas | |
| dc.title | Prior knowledge in evolutionary fuzzy recurrent controllers design | |
| dc.type | Objeto de conferencia | |
| dc.type | Objeto de conferencia | |
