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

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

A fuzzy Lyapunov function approach for stabilization and control of switched TS fuzzy systems

In this work, sufficient conditions for the existence of switching laws for stabilizing switched TS fuzzy systems via a fuzzy Lyapunov function are proposed. The conditions are found by exploring properties of the membership functions and are formulated in terms of linear matrix inequalities (LMIs). Stabilizing switching conditions with bounds on the decay rate solution and H1 performance are also obtained. Numerical examples illustrate the effectiveness of the proposed design methods.

Índice de sustentabilidade municipal: uma abordagem fuzzy para um sistema de apoio a decisão

Pós-graduação em Ciências Ambientais - Sorocaba

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

Pós-graduação em Engenharia Elétrica - FEIS

Fuzzy rule-based system for evaluation of uncertainty transaction in cassava chain

A fuzzy ruled-based system was developed in this study and resulted in an index indicating the level of uncertainty related to commercial transactions between cassava growers and their dealers. The fuzzy system was developed based on Transaction Cost Economics approach. The fuzzy system was developed from input variables regarding information sharing between grower and dealer on “Demand/purchase Forecasting”, “Production Forecasting” and “Production Innovation”. The output variable is the level of uncertainty regarding the transaction between seller and buyer agent, which may serve as a system for detecting inefficiencies. Evidences from 27 cassava growers registered in the Regional Development Offices of Tupa and Assis, São Paulo, Brazil, and 48 of their dealers supported the development of the system. The mathematical model indicated that 55% of the growers present a Very High level of uncertainty, 33% present Medium or High. The others present Low or Very Low level of uncertainty. From the model, simulations of external interferences can be implemented in order to improve the degree of uncertainty and, thus, lower transaction costs.

Modelo fuzzy estimando tempo de internação por doenças cardiovasculares

Abstract A fuzzy linguistic model based on the Mamdani method with input variables, particulate matter, sulfur dioxide, temperature and wind obtained from CETESB with two membership functions each was built to predict the average hospitalization time due to cardiovascular diseases related to exposure to air pollutants in São José dos Campos in the State of São Paulo in 2009. The output variable is the average length of hospitalization obtained from DATASUS with six membership functions. The average time given by the model was compared to actual data using lags of 0 to 4 days. This model was built using the Matlab v. 7.5 fuzzy toolbox. Its accuracy was assessed with the ROC curve. Hospitalizations with a mean time of 7.9 days (SD = 4.9) were recorded in 1119 cases. The data provided revealed a significant correlation with the actual data according to the lags of 0 to 4 days. The pollutant that showed the greatest accuracy was sulfur dioxide. This model can be used as the basis of a specialized system to assist the city health authority in assessing the risk of hospitalizations due to air pollutants.

Modelagem fuzzy aplicada a políticas públicas: proposta de um indice municipal de qualidade ambiental

Pós-graduação em Ciências Ambientais - Sorocaba

On the Newton method for solving fuzzy optimization problems

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Estimation of croplands using indicator kriging and fuzzy classification

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Um modelo fuzzy-dea-game para estratégias de produção sob incerteza

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)