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Forecasting the Demand of Short-Term Electric Power Load with Large-Scale LP-SVR

Smart Grid and Renewable Energy 2013年第6期4卷 449-457页

作者： Pablo Rivas-Perea j.an Cota-Ruiz David Garcia Chaparro Abel quezada Carreón francisco j. enríquez aguilera j.se-Gerardo Rosiles Department of Computer Science School of Engineering and Computer Science Baylor University Waco USA Department of Electrical and Computer Engineering Autonomous University of Ciudad Juárez (UACJ) Ciudad Juárez México Science Applica- tions International Corporation El Paso USA.

This research studies short-term electricity load prediction with a large-scalelinear programming support vector regression (LP-SVR) model. The LP-SVR is compared with other three non-linear regression models: Collobert’s SVR, Feed-Forward Neural Networks (FFNN), and Bagged Regression Trees (BRT). The four models are trained to predict hourly day-ahead loads given temperature predictions, holiday information and historical loads. The models are trained on-hourly data from the New England Power Pool (NEPOOL) region from 2004 to 2007 and tested on out-of-sample data from 2008. Experimental results indicate that the proposed LP-SVR method gives the smallest error when compared against the other approaches. The LP-SVR shows a mean absolute percent error of 1.58% while the FFNN approach has a 1.61%. Similarly, the FFNN method shows a 330 MWh (Megawatts-hour) mean absolute error, whereas the LP-SVR approach gives a 238 MWh mean absolute error. This is a significant difference in terms of the extra power that would need to be produced if FFNN was used. The proposed LP-SVR model can be utilized for predicting power loads to a very low error, and it is comparable to FFNN and over-performs other state of the art methods such as: Bagged Regression Trees, and Large-Scale SVRs.

关键词： Power Load Prediction Linear Programming Support Vector Regression Neural Networks for Regression Bagged Regression Trees

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Comprehensive Left Ventricular Mechanics Analysis by Speckle Tracking Echocardiography in COVID-19

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World j.urnal of Cardiovascular Diseases 2021年第2期11卷 113-125页

作者： francisco j. González-Ruiz Emmanuel A. Lazcano-Díaz Zuilma Y. Vásquez-Ortiz Fernanda Bernal-Ceballos Rodrigo Gopar-Nieto Consuelo Orihuela-Sandoval j.sé P. Hernández-Reyes Edgar García-Cruz Eduardo Bucio-Reta Ángel Ramos-enríquez Luis A. Cota-Apodaca Luis Efren-Santos Blanca Estela Broca-García Daniel Manzur-Sandoval Efrén Melano-Carranza Fernandez de la Reguera Guillermo Gustavo Roj.s-Velasco francisco Baranda-Tovar Department of Cardiovascular Critical Care National Institute of Cardiology “Dr. Ignacio Chávez” México City México Department of Echocardiography National Institute of Medical Science and Nutrition “Dr. Salvador Zubirán” México City México PhD Program National University of Mexico (UNAM) México City México Cardiovascular Diseases Department National Institute of Cardiology “Dr. Ignacio Chávez” México City México

Background: Cardiac involvement and the consequences of inflammation induced by SARS-CoV2 infection could have catastrophic long-term consequences. Left ventricular mechanics could identify a specific pattern of myoc... 详细信息

j.stify;"> Background: Cardiac involvement and the consequences of inflammation induced by SARS-CoV2 infection could have catastrophic long-term consequences. Left ventricular mechanics could identify a specific pattern of myocardial fiber damage in patients infected with COVID-19. To our knowledge there are no publications referring to the global description of ventricular mechanics in patients with COVID-19. Objective: To describe left ventricular mechanics in hospitalized patients with COVID-19. Methods: In this cross-sectional study, we included 40 hospitalized patients with confirmed diagnostic of COVID-19, from April 11, 2020, to September 6, 2020. Demographic and laboratory data, clinical and echocardiographic characteristics were collected, as well as events during hospitalization. Left ventricular deformation was analyzed and reported. Results: Subclinical dysfunction was observed in 82.5% (left ventricular longitudinal strain [LVGLS] -17.05% and global circumferential strain [GCS] -18.6%) of the patients, likewise, the mean twist and apical rotation were preserved, and even increased as part of the compensating mechanism to maintain the ejection fraction. Conclusion: In patients hospitalized with COVID-19, despite having a normal left ventricular ejection fraction, subclinical myocardial damage was found, manifested by a decrease in Global Longitudinal Strain (GLS) and Global Circumferential Strain (GCS). This behavior is similar to that of cardiomyopathies in the early stage of the disease, and given the pathophysiological mechanisms involved in the disease, its long-term consequences should be monitored and evaluated.

关键词： COVID-19 Speckle Tracking Echocardiography Myocarditis Cardiomyopa-thy Cardiac Mechanics Strain Myocardial Damage Deformation Imaging Myocardial Strain

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