Estimating the average length of hospitalization due to pneumonia: a fuzzy approach

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

Estimating outcomes in newborn infants using fuzzy logic

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

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).

Aplicação de sistemas neuro-fuzzy e espectrometria no infravermelho próximo para a identificação em tempo real do teor de nitrogênio foliar em cana-de-açúcar

Pós-graduação em Engenharia Elétrica - FEB

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.

On Switched Regulator Design of Uncertain Nonlinear Systems Using Takagi-Sugeno Fuzzy Models

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

Epidemiological Models of Directly Transmitted Diseases: An Approach via Fuzzy Sets Theory

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Analysis of Structural Integrity Using an ARTMAP-Fuzzy Artificial Neural Network

This paper presents the application of artificial neural networks in the analysis of the structural integrity of a building. The main objective is to apply an artificial neural network based on adaptive resonance theory, called ARTMAP-Fuzzy neural network and apply it to the identification and characterization of structural failure. This methodology can help professionals in the inspection of structures, to identify and characterize flaws in order to conduct preventative maintenance to ensure the integrity of the structure and decision-making. In order to validate the methodology was modeled a building of two walk, and from this model were simulated various situations (base-line condition and improper conditions), resulting in a database of signs, which were used as input data for ARTMAP-Fuzzy network. The results show efficiency, robustness and accuracy.

Simulação e controle de um quadcopter utilizando lógica fuzzy

The present work develops a model to simulate the dynamics of a quadcopter being controlled by a PD fuzzy controller. Initially is presented a brief history of quadcopters an introduction to fuzzy logic and fuzzy control systems. Afterwards is presented an overview of the quadcopter dynamics and the mathematical modelling development applying Newton-Euler method. Then the modelling are implemented in a Simulink model in addition to a PD fuzzy controller. A prototype proposition is made, by describing each necessary component to build up a quadcopter. In the end the results from the simulators are discussed and compared due to the discrepancy between the model using ideal sensor and the model using non-ideal sensors

Auxílio a tomada de decisão na inclusão de sobressalentes de manutenção em estoque utilizando um sistema especialista fuzzy

In the current economic scenario of constant changes, industries seek to increase their profitability decreasing inventory levels. Maintenance and maintenance management, combined with the inventory management of spare parts, has assumed a position of competitive advantage in business. Stock only what you need has become a difficult decision for managers, who are faced with the lack of models and criteria to assist this decision-making. This work proposes a method which supports decision making, on a MATLAB modeling, using criteria established by an expert and his maintenance workers team, focusing on no regular demand of spare parts. The proposed model was adequate to the needs of the company and the maintenance manager in the decision on the storage

Modelo de conjuntos fuzzy e de regressão logística para dados de obesidade

Obesidade e comumente definida como um excesso de gordura corporal, porém diante da dificuldade em mensurar tal gordura diretamente, esta tem sido definida como um excesso de peso mais do que um excesso de gordura corporal, que tem como desdobramento a ocorrência de doenças associadas e/ou prejuízos a saúde do indivíduo (4). Atualmente, o excesso de massa corpórea e verificado por meio de um Indice de Massa Corpórea (IMC), que considera o quociente entre o peso corporal (kg) e a estatura elevada ao quadrado (m2). Indivíduos com sobrepeso apresentam IMC de 25 at e 29; 9 kg=m2, e com obesidade apresentam IMC de 30 Kg=m2 ou mais, de acordo com a OMS (1). A identificação das causas da obesidade não é trivial e objetiva. Especialistas reconhecem que a obesidade e uma doença crônica, de difícil tratamento, denominada multifatorial, envolvendo em sua gênese diversos aspectos, entre eles: o consumo alimentar, aspectos ambientais, genéticos, psicossociais, entre outros. objetivo deste trabalho foi desenvolver um modelo baseado em teoria dos conjuntos Fuzzy para a classificação de obesidade levando em consideração as suas causas, e compará-lo com um modelo de regressão logística através da curva ROC. Para estudar as causas da obesidade na população de moradores da região do Distrito Sul de Campinas, foram coletados dados de uma amostra aleatória de 651 indivíuos, por meio de entrevista domiciliar. No primeiro estágio amostral, a partir do cadastro de domicílios residenciais dos agentes comunitários de saúde, foram aleatoriamente sorteados 920 domicílios (15% a mais do inicialmente previsto para cobrir perdas). Foram coletados dados de identificação geral, como: nome, idade, sexo, anos de escolaridade, tipo de ocupação e dados de consumo alimentar. O diagnóstico foi observado através do IMC. Num estudo preliminar, no modelo fuzzy foram consideradas como variáveis... (Resumo completo, clicar acesso eletrônico abaixo)

Estimação do risco de morte de recém-nascidos utilizando logica fuzzy tipo-2 intervalar

The main objective of the presented study is the development of a predictive interval type-2 fuzzy inference system in order to estimate the mortality risk for a newborn, to be used as an auxiliary tool for decision making in medical centers where there is a lack of professionals for this purpose and, afterwards, to compare its performance to a type-1 fuzzy system. The input variables were chosen due to their acquisition ‘simplicity, not involving any invasive tests, such as blood tests or other specific tests. The variables are easily obtained in the first few minutes of life: birth weight, gestational age at delivery, 5-minute Apgar score and previous report of stillbirth. Databases from the DATASUS were used to validate the model. 1351 records from the city of São José dos Campos, a mid-sized city in the São Paulo state’s countryside, were considered in this study. Finally, an analysis using the ROC curve was performed to estimate the model’s accuracy

Estimação do número de internações por doenças respiratórias utilizando lógica fuzzy tipo-2 intervalar

In this work was developed a fuzzy computational model type-2 predictive interval, using the software of the type-2 fuzzy MATLAB toolbox, the final idea is to estimate the number of hospitalizations of patients with respiratory diseases. The interest in the creation of this model is to assist in decision makeshift hospital environment, where there are no medical or professional equipment available to provide the care that the population need. It began working with the study of fuzzy logic, the fuzzy inference system and fuzzy toolbox. Through a real database provided by the Departamento de Informática do Sistema Único de Saúde (DATASUS) and Companhia de Tecnologia de Saneamento Básico (CETESB), was possible to start the model. The analyzed database is composed of the number of patients admitted with respiratory diseases a day for the public hospital in São José dos Campos, during the year 2009 and by factors such as PM10, SO2, wind and humidity. These factors were analyzed as input variables and, through these, is possible to get the number of admissions a day, which is the output variable of the model. For data analysis we used the fuzzy control method type-2 Mamdani. In the following steps the performance developed in this work was compared with the performance of the same model using fuzzy logic type-1. Finally, the validity of the models was estimated by the ROC curve

Projeto de um Multiplicador Divisor Anal´ogico em tecnologia CMOS para uso em controlador fuzzy tipo-2 intervalar

The main objective of the presented study is the design of a analog multiplier-divider as integrant part of the type-reducer circuit of type-2 fuzzy controller chip. The proposed circuit is a multiplier/divider which operates in current mode, in the CMOS technology with a supply voltage of 1.8 V.The circuit simulation was performed in PSPICE software with simulation model provided by AMS (Austria Mikro Systems International) in CMOS technology 0.35μm

Controle fuzzy de um motor dc utilizando sistema de aquisição de dados e o matlab

The present work develops a fuzzy inference system to control the rotation speed of a DC motor available in Degem Kit. Therefore, it should use the fuzzy toolbox of Matlab in conjunction with the data acquisition board NI - USB - 6009, a National Instrument’s board. An introduction to fuzzy logic, the mathematical model of a DC motor and the operation of data acquisition board is presented first. Followed by the controller fuzzy model implemented using Simulink which is described in detail. Finally, the prototype is shown and the simulator results are presented