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Wilson Tsakane Mongwe, Rendani Mbuvha and Tshilidzi Marwala
Markov chain Monte Carlo (MCMC) techniques are usually used to infer model parameters when closed-form inference is not feasible, with one of the simplest MCMC methods being the random walk Metropolis?Hastings (MH) algorithm. The MH algorithm suffers fro...
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Qiao Yan, Xiaoqian Liu, Xiaoping Deng, Wei Peng and Guiqing Zhang
Prediction of energy use behaviors is a necessary prerequisite for designing personalized and scalable energy efficiency programs. The energy use behaviors of office occupants are different from those of residential occupants and have not yet been studie...
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Edilson Marcelino Silva, Thais Destefani Ribeiro Furtado, Ariana Campos Frühauf, Joel Augusto Muniz, Tales Jesus Fernandes
Pág. e46893
Zinc uptake is essential for crop development; thus, knowledge about soil zinc availability is fundamental for fertilization in periods of higher crop demand. A nonlinear first-order kinetic model has been employed to evaluate zinc availability. Studies ...
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Lisa Maria Ringel, Márk Somogyvári, Mohammadreza Jalali and Peter Bayer
Fractures serve as highly conductive preferential flow paths for fluids in rocks, which are difficult to exactly reconstruct in numerical models. Especially, in low-conductive rocks, fractures are often the only pathways for advection of solutes and heat...
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Leonilce Mena, Marinho Gomes de Andrade Filho
Pág. 1755 - 1760
Neste artigo apresentamos uma ramificação do processo auto-regressivo de primeira ordem com coeficiente aleatório e variante no tempo, assumindo uma estrutura de dependência dos coeficientes aleatórios, que leva a um modelo de filtro de Kalman adaptado. ...
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