Automatic Generation Of Fuzzy Rules
Mostrando 1-7 de 7 artigos, teses e dissertações.
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1. Geração genética de classificador fuzzy intervalar do tipo-2
The objective of this work is to study, expand and evaluate the use of interval type-2 fuzzy sets in the knowledge representation for fuzzy inference systems, specifically for fuzzy classifiers, as well as its automatic generation form data sets, by means of genetic algorithms. This work investigates the use of such sets focussing the issue of balance betwee
Publicado em: 2009
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2. Rede Neural Difusa com T-normas Diferenciáveis e Interativas
Fuzzy sets are used in the representation of vague and imprecise knowledge. Neural networks, besides their computational parallelism, also have learning capabilities. The combination of such both paradigms is an attempt to congregate their benefits in an integrated system, such a fuzzy neural network. T-norms are functions that actuate like intersection and
Publicado em: 2007
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3. Geração genética de Regras Fuzzy com pré-seleção de Regras Candidatas.
A construção da base de regras está entre as tarefas mais importantes e complexas na modelagem de Sistemas Fuzzy. As bases de regras fuzzy podem ser definidas a partir do conhecimento obtido de especialistas humanos. Entretanto, esta e uma tarefa bastante difícil e desafiadora e pode se tornar impossível para problemas complexos que apresentam muitas va
Publicado em: 2007
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4. HIBRID NEURO-FUZZY-GENETIC SYSTEM FOR AUTOMATIC DATA MINING / SISTEMA HÍBRIDO NEURO-FUZZY-GENÉTICO PARA MINERAÇÃO AUTOMÁTICA DE DADOS
This dissertation presents the proposal and the development of a totally automatic data mining system. The main objective is to create a system that is capable of extracting obscure information from complex databases, without demanding the presence of a technical specialist to configure it. The Hierarchical Neuro-Fuzzy Binary Space Partitioning model (NFHB)
Publicado em: 2004
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5. Um paradigma baseado em algoritmos genéticos para o aprendizado de regras Fuzzy.
A construção da base de conhecimento de sistemas fuzzy tem sido beneficiada intensamente por métodos automáticos que extraem o conhecimento necessário a partir de conjuntos de dados que representam exemplos do problema. A computação evolutiva, em particular os algoritmos genéticos, tem sido alvo de um grande número de pesquisas que tratam, usando ab
Publicado em: 2004
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6. HIERARQUICAL NEURO-FUZZY MODELS BASED ON REINFORCEMENT LEARNING FOR INTELLIGENT AGENTS / NOVOS MODELOS NEURO-FUZZY HIERÁRQUICOS COM APRENDIZADO POR REFORÇO PARA AGENTES INTELIGENTES
This thesis investigates neuro-fuzzy hybrid models for automatic learning of actions taken by agents. The objective of these models is to provide an agent with intelligence, making it capable of acquiring and retaining knowledge and of reasoning (infer an action) by interacting with its environment. Learning in these models is performed by a non-supervised p
Publicado em: 2003
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7. Obtenção das funções de pertinência de um sistema neurofuzzy modificado pela rede de Kohonen
This dissertation presents an hybrid computational model that combines fuzzy system techniques and artificial neural networks. Its objective is the automatic generation of membership functions, in particular, triangle forms, aiming at a dynamic modelling of a system. The model is named Neo-Fuzzy-Neuron Modify by Kohonen (NFN-MK), since it starts using Kohone
Publicado em: 2003