A hierarchy of adaptive (X)over-bar control charts

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Fuzzy logic to predict thermal damages of ground parts

One of the critical problems in implementing an intelligent grinding process is the automatic detection of workpiece surface burn. This work uses fuzzy logic as a tool to classify and predict burn levels in the grinding process. Based on acoustic emission signals, cutting power, and the mean-value deviance (MVD), linguistic rules were established for the various burn situations (slight, intermediate, severe) by applying fuzzy logic using the Matlab Toolbox. Three practical fuzzy system models were developed. The first model with two inputs resulted only in a simple analysis process. The second and third models have an additional MVD statistic input, associating information and precision. These two models differ from each other in terms of the rule base developed. The three developed models presented valid responses, proving effective, accurate, reliable and easy to use for the determination of ground workpiece burn. In this analysis, fuzzy logic translates the operator's human experience associated with powerful computational methods.

Traffic flow breakdown prediction using feature reduction through Rough-Neuro fuzzy Networks

The prediction of the traffic behavior could help to make decision about the routing process, as well as enables gains on effectiveness and productivity on the physical distribution. This need motivated the search for technological improvements in the Routing performance in metropolitan areas. The purpose of this paper is to present computational evidences that Artificial Neural Network ANN could be use to predict the traffic behavior in a metropolitan area such So Paulo (around 16 million inhabitants). The proposed methodology involves the application of Rough-Fuzzy Sets to define inference morphology for insertion of the behavior of Dynamic Routing into a structured rule basis, without human expert aid. The dynamics of the traffic parameters are described through membership functions. Rough Sets Theory identifies the attributes that are important, and suggest Fuzzy relations to be inserted on a Rough Neuro Fuzzy Network (RNFN) type Multilayer Perceptron (MLP) and type Radial Basis Function (RBF), in order to get an optimal surface response. To measure the performance of the proposed RNFN, the responses of the unreduced rule basis are compared with the reduced rule one. The results show that by making use of the Feature Reduction through RNFN, it is possible to reduce the need for human expert in the construction of the Fuzzy inference mechanism in such flow process like traffic breakdown. © 2011 IEEE.

Classificação da curvatura de vertentes em perfil via Thin Plate Spline e Inferência Fuzzy

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Aplicando lógica fuzzy no controle de robôs móveis usando dispositivos lógicos programáveis e a linguagem VHDL

Pós-graduação em Engenharia Elétrica - FEIS

Formulação do controle preventivo em sistemas de distribuição de energia elétrica baseada na lógica fuzzy e redes neurais

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Uma contribuição da aplicação de modelos fuzzy empregados na detecção da queima de peças na retificação plana

Pós-graduação em Engenharia Mecânica - FEB

Maternidade e práticas de saúde: o instituído e o possível

Pós-graduação em Psicologia - FCLAS

Rede Neuro-Fuzzy-Wavelet para detecção e classificação de anomalias de tensão em sistemas elétricos de potência

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Modelo fuzzy para obtenção do tempo de aeração em silos verticais visando reduzir o consumo de energia elétrica

Pós-graduação em Agronomia (Energia na Agricultura) - FCA

Sistema fuzzy de suporte a decisão para aplicação de programa de eficiência energética em serrarias

Pós-graduação em Agronomia (Energia na Agricultura) - FCA

A Lógica Fuzzy Aplicada à Recuperação de Informação

The information retrieval process involves subjective, imprecise and vague concepts, such as "information need", "relevance", and the very concept of "information". The main information retrieval models treat these concepts accurately, represented by a single numerical value. The fuzzy logic, while operating with the uncertainty of natural phenomena in a systematic and rigorous manner, represents a promising alternative to solve some problems related to information retrieval. This paper presents the fuzzy logic and some examples of its use in information retrieval systems (IRS).

A Fuzzy Goal Programming model for solving aggregate production-planning problems under uncertainty: A case study in a Brazilian sugar mill

This paper proposes a Fuzzy Goal Programming model (FGP) for a real aggregate production-planning problem. To do so, an application was made in a Brazilian Sugar and Ethanol Milling Company. The FGP Model depicts the comprehensive production process of sugar, ethanol, molasses and derivatives, and considers the uncertainties involved in ethanol and sugar production. Decision-makings, related to the agricultural and logistics phases, were considered on a weekly-basis planning horizon to include the whole harvesting season and the periods between harvests. The research has provided interesting results about decisions in the agricultural stages of cutting, loading and transportation to sugarcane suppliers and, especially, in milling decisions, whose choice of production process includes storage and logistics distribution. (C)2014 Elsevier B.V. All rights reserved.

Modelo de avaliação de impacto ambiental utilizando a teoria dos conjuntos fuzzy: um estudo de caso para a indústria automobilística

Pós-graduação em Ciências Ambientais - Sorocaba

Desenvolvimento de uma rede neuro-fuzzy para a previsão da carga

Pós-graduação em Engenharia Elétrica - FEIS