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A Novel Multilevel-SVD Method to Improve Multistep Ahead Forecasting in Traffic Accidents Domain
ArticleAbstract: Here is proposed a novel method for decomposing a nonstationary time series in components of low andPalabras claves:Autores:Lida Barba, Nibaldo RodríguezFuentes:googlescopusCirculant singular value decomposition combined with a conventional neural network to improve the hake catches prediction
Conference ObjectAbstract: This paper presents the one-step ahead forecasting of time series based on Singular Value DecompositPalabras claves:Autores:DIEGO GUILLERMO BARBA MAGGI, Lida Barba, Nibaldo RodríguezFuentes:googlescopusCombining multi-scalewavelet entropy and kernelized classification for bearing multi-fault diagnosis
ArticleAbstract: Discriminative feature extraction and rolling element bearing failure diagnostics are very importantPalabras claves:Kernel Extreme Learning Machine, Multi-scale entropy, Stationary Wavelet TransformAutores:Alvarez P., Cabrera-Guerrero G., Lida Barba, Nibaldo RodríguezFuentes:googlescopusHybrid models based on singular values and autoregressive methods for multistep ahead forecasting of traffic accidents
ArticleAbstract: The traffic accidents occurrence urges the intervention of researchers and society; the human lossesPalabras claves:Autores:Lida Barba, Nibaldo RodríguezFuentes:googlescopusForecast of traffic accidents based on components extraction and an autoregressive neural network with levenberg-marquardt
Conference ObjectAbstract: In this paper is proposed an improved one-step-ahead strategy for traffic accidents and injured forePalabras claves:Autoregressive Neural Network, Levenberg-Marquardt, SINGULAR VALUE DECOMPOSITIONAutores:Lida Barba, Nibaldo RodríguezFuentes:googlescopusImproved forecasting of CO<inf>2</inf> emissions based on an ANN and multiresolution decomposition
Conference ObjectAbstract: The sustainability of the environment is a shared goal of the United Nations. In this context, the fPalabras claves:Artificial Neural Network, Carbon dioxide, forecasting, Multiresolution decomposition, Stationary Wavelet TransformAutores:Lida Barba, Nibaldo RodríguezFuentes:googlescopusSmoothing strategies combined with ARIMA and neural networks to improve the forecasting of traffic accidents
ArticleAbstract: Two smoothing strategies combined with autoregressive integrated moving average (ARIMA) and autoregrPalabras claves:Autores:Lida Barba, Montt C., Nibaldo RodríguezFuentes:googlescopusStationary wavelet-Fourier entropy and kernel extreme learning for bearing multi-fault diagnosis
ArticleAbstract: Bearing fault diagnosis methods play an important role in rotating machine health monitoring. In recPalabras claves:Fourier amplitude spectrum kernel extreme learning machine, Multi-scale entropy, Stationary wavelet packet transformAutores:Alvarez P., Cabrera-Guerrero G., Lida Barba, Nibaldo RodríguezFuentes:googlescopusThe potential of non-invasive pre- and post-mortem carcass measurements to predict the contribution of carcass components to slaughter yield of guinea pigs
ArticleAbstract: Guinea pig meat consumption is increasing exponentially worldwide. The evaluation of the contributioPalabras claves:Carcass component, Carcass quality, Guinea pig, pbkp_rediction modelAutores:Davinia Sánchez-Macías, Iván Barba, Lida Barba, Nibaldo RodríguezFuentes:googlescopusMultiscale forecasting models
BookAbstract: This book presents two new decomposition methods to decompose a time series in intrinsic componentsPalabras claves:artificial neural networks, forecasting, Hankel matrix, Singular spectrum analysis, SINGULAR VALUE DECOMPOSITION, Stationary wavelet decomposition, TIME SERIESAutores:Lida BarbaFuentes:googlescopus