GA-TSKfnn: Parameters tuning of fuzzy neural network using genetic algorithms
- 1 November 2005
- journal article
- research article
- Published by Elsevier BV in Expert Systems with Applications
- Vol. 29 (4), 769-781
- https://doi.org/10.1016/j.eswa.2005.06.001
Abstract
No abstract availableKeywords
This publication has 27 references indexed in Scilit:
- Popfnn-cri(s): pseudo outer product based fuzzy neural network using the compositional rule of inference and singleton fuzzifierIEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), 2003
- MCMAC–CVT: a novel on-line associative memory based CVT transmission control systemNeural Networks, 2002
- Generating the knowledge base of a fuzzy rule-based system by the genetic learning of the data baseIEEE Transactions on Fuzzy Systems, 2001
- Improved MCMAC with momentum, neighborhood, and averaged trapezoidal outputIEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), 2000
- Performance evaluation of fuzzy classifier systems for multidimensional pattern classification problemsIEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), 1999
- A two-stage evolutionary process for designing TSK fuzzy rule-based systemsIEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), 1999
- Evolving fuzzy rule based controllers using genetic algorithmsFuzzy Sets and Systems, 1996
- Tuning fuzzy logic controllers by genetic algorithmsInternational Journal of Approximate Reasoning, 1995
- Simultaneous design of membership functions and rule sets for fuzzy controllers using genetic algorithmsIEEE Transactions on Fuzzy Systems, 1995
- THE USE OF MULTIPLE MEASUREMENTS IN TAXONOMIC PROBLEMSAnnals of Eugenics, 1936