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Your search keyword '"Alanis, Alma Y."' showing total 102 results
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102 results on '"Alanis, Alma Y."'

6. Passivity-Based Inverse Optimal Impulsive Control for Influenza Treatment in the Host.

Author

Hernandez-Mejia, Gustavo, Alanis, Alma Y., Hernandez-Gonzalez, Miguel, Findeisen, Rolf, and Hernandez-Vargas, Esteban A.

Subjects
MONTE Carlo method, H1N1 influenza, INFLUENZA, VIRUS diseases, INFLUENZA A virus
Abstract

Influenza A virus infections are causes of severe illness resulting in high levels of mortality. Neuraminidase inhibitors such as zanamivir and oseltamivir are used to treat influenza; however, treatment recommendations remain debatable. In this paper, a discrete-time inverse optimal impulsive control scheme based on passivation is proposed to address the antiviral treatment scheduling problem. We adapt results regarding stability, passivity, and optimality for the impulsive action. The study is founded on mathematical models whose parameters are adjusted to data from clinical trials where participants were experimentally infected with influenza H1N1 and treated with either zanamivir or oseltamivir. Simulation results show that control-based techniques can reduce the amount of medication while simultaneously reach the efficacy levels of the treatment schedules by the Food and Drug Administration. Monte Carlo simulations disclose the robustness of the proposed control-based techniques. [ABSTRACT FROM AUTHOR]

Published
2020
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21. Hyperellipsoidal neuron

Author

Villasenor, Carlos, primary, Arana-Daniel, Nancy, additional, Alanis, Alma Y., additional, and Lopez-Franco, Carlos, additional

Published
2017
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26. Electricity Prices Forecasting using Artificial Neural Networks.

Author

Alanis, Alma Y.

Abstract

This paper presents the results of the use of training algorithms for recurrent neural networks based on the extended Kalman filter and its use in electric energy price prediction, for both cases: one-step ahead and n-step ahead. In addition, it is included the stability proof using the well-known Lyapunov methodology, for the proposed artificial neural network trained with an algorithm based on the extended Kalman filter. Finally, the applicability of the proposed prediction scheme is shown by mean of the one-step ahead and n-step ahead prediction using data from the European power system. [ABSTRACT FROM PUBLISHER]

Published
2018
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