Pruning for Interpretability of Large Spanned eTS



On-line Learning Algorithms

Related Project

CLASSE - Classificação Sintética para Supervisão Industrial (Synthetic Classification for Industrial Supervision)


2nd International Symposium on Evolving Fuzzy Systems, EFS\'06, September 2006

Cited by

Year 2013 : 1 citations

 Studies in Fuzziness and Soft Computing, Volume 274
J Kacprzyk - Springer

Year 2012 : 1 citations

 Navigating interpretability issues in evolving fuzzy systems
E Lughofer - Scalable Uncertainty Management, 2012 - Springer

Year 2011 : 2 citations

 Evolving fuzzy systems-Methodologies, advanced concepts and applications
E Lughofer - 2011 -

 On-line elimination of local redundancies in evolving fuzzy systems
E Lughofer, JL Bouchot, A Shaker - Evolving Systems, 2011 - Springer

Year 2010 : 1 citations

 1. Evolving fuzzy optimally pruned extreme learning machine for regression problems 2010 FM Pouzols… - Evolving Systems - Springer
Abstract This paper proposes an approach to the iden- tification of evolving fuzzy Takagi–Sugeno
systems based on the optimally pruned extreme learning machine (OP-ELM) methodology.

Year 2009 : 1 citations

 Sensor virtual adaptable de concentración de etanol para Fermentadores Industriales
B Martínez, F Herrera, L Peralta - … de Automática e Informática Industrial RIAI, 2009 - Elsevier