A carregar...
Publicação
Training neuro-fuzzy models using evolution based algorithms
| Nome: | Descrição: | Tamanho: | Formato: | |
|---|---|---|---|---|
| 29.03 KB | Adobe PDF |
Orientador(es)
Resumo(s)
The normal design process for neural networks or fuzzy
systems involve two different phases: the determination
of the best topology, which can be seen as a system
identification problem, and the determination of its
parameters, which can be envisaged as a parameter
estimation problem. This latter issue, the determination
of the model parameters (linear weights and interior
knots) is the simplest task and is usually solved using
gradient or hybrid schemes. The former issue, the
topology determination, is an extremely complex task,
especially if dealing with real-world problems.
Descrição
Palavras-chave
Constructive algorithms B-splines Bacterial programming Genetic programming Memetic algorithms
Contexto Educativo
Citação
Cabrita, C.; Ruano, A. E.; Fonseca, C. M. Training neuro-fuzzy models using evolution based algorithms, Trabalho apresentado em Global Education Techology Symposium (GETS 2006), In Proceedings of the Global Education Techology Symposium (GETS 2006), Faro, 2006.