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Edgar Acuna, Roxana Aparicio and Velcy Palomino
In this paper we investigate the effect of two preprocessing techniques, data imputation and smoothing, in the prediction of blood glucose level in type 1 diabetes patients, using a novel deep learning model called Transformer. We train three models: XGB...
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Miaomiao Yu, Hongyong Yuan, Kaiyuan Li and Lizheng Deng
To separate the noise and important signal features of the indoor carbon dioxide (CO2) concentration signal, we proposed a noise cancellation method, based on time-varying, filtering-based empirical mode decomposition (TVF-EMD) with Bayesian optimization...
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Chang-Yong Song
Meta-model sre generally applied to approximate multi-objective optimization, reliability analysis, reliability based design optimization, etc., not only in order to improve the efficiencies of numerical calculation and convergence, but also to facilitat...
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Igor Vujovic, Jo?ko ?oda, Ivica Kuzmanic and Miro Petkovic
Nowadays, the impact of the ships on the World economy is enormous, considering that every ship needs fuel to sail from source to destination. It requires a lot of fuel, and therefore, there is a need to monitor and predict a ship?s average fuel consumpt...
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Eduardo Campos, Rubens Penha Cysne
Pág. 5 - 38
Este artigo avalia a sustentabilidade da dívida pública brasileira usando dados mensais de janeiro de 2003 a junho de 2016 com base na estimação de funções de reação fiscal cujos coeficientes variam ao longo do tempo. Consideramos três métodos de estimaç...
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Rafael Barros de Rezende
Pág. 27 - 49
This paper compares the interpolation abilities of nonparametric and parametric term structure models which are widely used by the main Central Banks of the world. Seeking the combination of smoothness and flexibility, a new Nelson-Siegel class model is ...
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Brian J. Reich, Curtis B. Storlie, Howard D. Bondell
Pág. 110 - 120
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Yanagihara, H. Ohtaki, M.
Pág. 771 - 786
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