Fuzzy Rules Extraction
Mostrando 1-8 de 8 artigos, teses e dissertações.
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1. HYBRID SYSTEM FOR RULE EXTRACTION APPLIED TO DIAGNOSIS OF POWER TRANSFORMERS / SISTEMA HÍBRIDO DE EXTRAÇÃO DE REGRAS APLICADO A DIAGNÓSTICO DE TRANSFORMADORES
Este trabalho tem como objetivo construir um classificador baseado em regras de inferência fuzzy, as quais são extraídas a partir de máquinas de vetor suporte (SVMs) e ajustadas com o auxílio de um algoritmo genético. O classificador construído visa a diagnosticar transformadores de potência. As SVMs são sistemas de aprendizado baseados na teoria do
IBICT - Instituto Brasileiro de Informação em Ciência e Tecnologia. Publicado em: 10/09/2012
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2. FUZZY MODELS IN SEGMENTATION AND ANALYSIS OF BANK MARKETING / MODELOS FUZZY NA SEGMENTAÇÃO E ANÁLISE DO MERCADO BANCÁRIO
Este trabalho tem como principal objetivo propor e desenvolver uma metodologia baseada em modelos fuzzy para a segmentação e caracterização dos segmentos que compõem o mercado bancário, permitindo um amplo conhecimento dos perfis de clientes, melhor adaptação das ofertas ao mercado e, conseqüentemente, melhores retornos financeiros. A metodologia pr
Publicado em: 2008
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3. 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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4. FUZZY RULES EXTRACTION FROM SUPPORT VECTOR MACHINES (SVM) FOR MULTI-CLASS CLASSIFICATION / EXTRAÇÃO DE REGRAS FUZZY PARA MÁQUINAS DE VETOR SUPORTE (SVM) PARA CLASSIFICAÇÃO EM MÚLTIPLAS CLASSES
This text proposes a new method for fuzzy rule extraction from support vector machines (SVMs) trained to solve classification problems. SVMs are learning systems based on statistical learning theory and present good ability of generalization in real data base sets. These systems have been successfully applied to a wide variety of application. However SVMs, a
Publicado em: 2006
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5. 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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6. 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
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7. TRAFFIC CONTROL THROUGH FUZZY LOGIC AND NEURAL NETWORKS / CONTROLE DE SEMÁFOROS POR LÓGICA FUZZY E REDES NEURAIS
This work presents the use of fuzzy logic and neural networks in the development of a traffic signal controller - FUNNCON. The work consists of four main sections: study of traffic engineering fundamentals; definition of a methodology for evaluation of traffic controls; definition of the proposed controller model; and implementation on a case study using rea
Publicado em: 2002
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8. NEURO-FUZZY BSP HIERARCHICAL SYSTEM FOR TIME FORECASTING AND FUZZY RULE EXTRACTION DOR DATA MINING APPLICATONS / SISTEMA NEURO-FUZZY HIERÁRQUICO BSP PARA PREVISÃO E EXTRAÇÃO DE REGRAS FUZZY EM APLICAÇÕES DE DATA MINING
This dissertation investigates the use of a Neuro-Fuzzy Hierarchical system for time series forecasting and fuzzy rule extraction for Data Mining applications. The objective of this work was to extend the Neuro-Fuzzy BSP Hierarchical model for the classification of registers and time series forecasting. The process of classification of registers in the Data
Publicado em: 2000