Navegando por Assunto "Bayesian inference"

Agora exibindo 1 - 4 de 4

Acesso aberto (Open Access)
Estratégia de otimização para a melhoria da interpretabilidade de redes bayesianas: aplicações em sistemas elétricos de potência
(Universidade Federal do Pará, 2009-12-10) ROCHA, Cláudio Alex Jorge da; FRANCÊS, Carlos Renato Lisboa; http://lattes.cnpq.br/7458287841862567
The study of methods, techniques and tools that can aid the decision processes in power systems, in its many sections, is a subject of great interest. This decision support can be accomplished through many different techniques, particularly those based on computational intelligence, given their applicability on domains with uncertainty. In this proposal, Bayesian networks are used for the extraction of knowledge models from the available data on power systems. Moreover, given the demands of these systems and some limitations imposed to the inferences in Bayesian networks, a method is proposed, using genetic algorithms, capable of extending the power of comprehensibility of the patterns discovered; it aims at finding the optimal scenario in order to attain a given target, considering the incorporation of a priori knowledge from domain specialists, identifying the most influent variables in the domain for the maximization of the target variable.
Acesso aberto (Open Access)
Inserção da temperatura no modelo de Langmuir aplicado na adsorção de íons cobre por zeólita 5A : experimental e estatística Bayesiana
(Universidade Federal do Pará, 2025-02-05) SOUSA, Ana Paula Souza de; RODRIGUES, Emerson Cardoso; http://lattes.cnpq.br/7459428211048580; HTTPS://ORCID.ORG/0000-0002-0303-4578; ESTUMANO, Diego Cardoso; http://lattes.cnpq.br/5521162828533153; https://orcid.org/0000-0003-4318-4455
The treatment of wastewater contaminated by heavy metals represents a significant environmental challenge, with adsorption being one of the main approaches for removing these contaminants, as it exhibits high efficiency in molecular separation. Understanding the interaction between adsorbent and adsorbate is essential for predicting dynamics under different operational conditions. Thus, the use of modeling techniques in isotherm prediction allows for estimating adsorption performance, reducing the need for intensive experimentation, while promoting process optimization. Considering these factors, this work aimed to develop a predictive model capable of estimating adsorption isotherms of copper ions by zeolite 5A at different temperatures. The methodology involved the production and characterization of kaolin waste, metakaolin, and the zeolitic product, utilizing characterization techniques such as X-ray Fluorescence Spectrometry (XRF), X-ray Diffraction (XRD), Scanning Electron Microscopy (SEM), and thermal analyses, including Thermogravimetry (TG), Differential Thermogravimetry (DTG), and Differential Scanning Calorimetry (DSC), to determine the chemical and mineralogical composition, morphology, and thermal stability of the material. Adsorption isotherms of copper ions were performed at temperatures of 25 ºC, 35 ºC, 45 ºC, 55 ºC, 65 ºC, 75 ºC, 85 ºC, and 95 ºC. To study the adsorption mechanisms and the adsorbent/adsorbate interaction, the Markov Chain Monte Carlo (MCMC) method with the Metropolis-Hastings algorithm was used to estimate model parameters and subsequently fit them to the experimental data. Based on these data, the Langmuir model was adapted to incorporate temperature, in the range of 25 ºC to 150 ºC, followed by the calibration, validation, and prediction of adsorption dynamics. The characterization results confirmed the potential use of kaolinitic waste for zeolite synthesis, as well as the successful formation of zeolite 5A through its chemical composition, mineralogy, and morphology. The isotherms revealed that copper removal capacity increased proportionally with temperature, obtaining a maximum adsorption capacity of 754.85 mg/g at 95 ºC. The parameter estimation validated the adaptation of the Langmuir model for different thermal conditions, which proved effective in predicting the isotherms, optimizing the adsorption process at different temperatures, and providing a good model estimate, thus enabling the reduction of extensive experimental activities.
Acesso aberto (Open Access)
Selectivity curves of the capture of mangrove crab (Ucides cordatus) on the northern coast of Brazil using bayesian inference
(Instituto Internacional de Ecologia, 2016-06) FURTADO JUNIOR, Ivan; ABRUNHOSA, Fernando Araujo; HOLANDA, Francisco Carlos Alberto Fonteles; TAVARES, Marcia Cristina da Silva
Fishing selectivity of the mangrove crab Ucides cordatus in the north coast of Brazil can be defined as the fisherman's ability to capture and select individuals from a certain size or sex (or a combination of these factors) which suggests an empirical selectivity. Considering this hypothesis, we calculated the selectivity curves for males and females crabs using the logit function of the logistic model in the formulation. The Bayesian inference consisted of obtaining the posterior distribution by applying the Markov chain Monte Carlo (MCMC) method to software R using the OpenBUGS, BRugs, and R2WinBUGS libraries. The estimated results of width average carapace selection for males and females compared with previous studies reporting the average width of the carapace of sexual maturity allow us to confirm the hypothesis that most mature individuals do not suffer from fishing pressure; thus, ensuring their sustainability.
Acesso aberto (Open Access)
Variabilidade genética do peso ao nascer e seleção para crescimento em bubalinos do estado do Pará, Brasil
(Instituto Nacional de Pesquisas da Amazônia, 2014-09) AGUIAR, Juliana Flor de; MARCONDES, Cíntia Righetti; MARQUES, José Ribamar Felipe; VOZZI, Pedro Alejandro; CAMARGO JÚNIOR, Raimundo Nonato Colares; MARQUES, Larissa Coelho; ARAÚJO, Ronyere Olegário de; GUNSKI, Ricardo José
Birth weight is a performance parameter of great zootechnical importance for both meat and dairy production, as well as for breeding animals, mainly due to its relation to survival rate at weaning, and the weight of animals throughout their developmental and growth phases. Therefore, the objective of this work was to establish heritability estimates, as well as phenotypic and genetic trends of birth weight of water buffaloes from State of Pará, Brazil. Descriptive statistics were calculated and the Shapiro-Wilk Normality test was performed with a Statistical Analysis System package. Heritability estimates were established by Bayesian inference. BW was 36.6 kg in average. The statistical model considered sex, year of birth and breed composition of the animals as fixed effects, and animal, maternal and residual as random effects. Direct heritability was platykurtic (flattened) and with higher asymmetry, presenting a bimodal distribution with the first mode close to 0.10, and the second mode close to 0.30; the maternal heritability was trimodal, with peaks very close to 0.15, and another, less evident, close to 0.20. The direct genetic trend of birth weight was negative (-0.03kg year-1) and maternal genetic trend was close to zero (0.001kg ano-1), even though the phenotypic trend had been positive (0.156 kg year-1). There is genetic variability to be addressed in a breeding program, however, very little was done as far as selection for growth of water buffaloes in the State of Pará.