Modelos Computacionais Fuzzy Para Avaliar Efeitos Da Poluição Do Ar Em Crianças

Abstract

Objective: To build a fuzzy computational model to estimate the number of hospitalizations of children aged up to 10 years due to respiratory conditions based on pollutants and climatic factors in the city of São José do Rio Preto, Brazil.Methods: A computational model was constructed using the fuzzy logic. The model has 4 inputs, each with 2 membership functions generating 16 rules, and the output with 5 pertinence functions, based on the Mamdani’s method, to estimate the association between the pollutants and the number of hospitalizations. Data from hospitalizations, from 2011-2013, were obtained in DATASUS - and the pollutants Particulate Matter (PM10) and Nitrogen Dioxide (NO2), wind speed and temperature were obtained by the Environmental Company of São Paulo State (Cetesb).Results: A total of 1,161 children were hospitalized in the period and the mean of pollutants was 36 and 51 µg/m3 - PM10 and NO2, respectively. The best values of the Pearson correlation (0.34) and accuracy measured by the Receiver Operating Characteristic (ROC) curve (NO2 - 96.7% and PM10 - 90.4%) were for hospitalizations on the same day of exposure.Conclusions: The model was effective in predicting the number of hospitalizations of children and could be used as a tool in the hospital management of the studied region.

Metodologia Para Elaboração De Um Sistema Fuzzy Na Obtenção Do Índice De Conicidade Em Adultos

“…Ao contrário do IMC, que não diferencia entre massa muscular, osso e gordura, o IC pode ser uma ferramenta útil para identificar indivíduos com obesidade central (SHENOY; JAGADAMBA, 2017). David et al (2018) realizaram um estudo com o objetivo de construir um modelo computacional fuzzy para estimar o número de internações de crianças até 10 anos devido a doenças respiratórias, utilizando dados de poluentes e fatores climáticos da cidade de São José do Rio Preto, Brasil. O modelo mostrou-se eficaz na predição do número de internações de crianças, sendo indicada sua utilização no âmbito hospitalar da região estudada, pois trata-se de um modelo de baixo custo e prático.…”

Optimization of Markov Weighted Fuzzy Time Series Forecasting Using Genetic Algorithm (GA) and Particle Swarm Optimization (PSO)

“…calculate data using ordinary time series methods. This method is widely used in the fields of financial forecasting [10], air pollution [11], and temperature [12]. The development of the Fuzzy Times Series method has been widely carried out.…”