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A new algorithm for computing disjoint orthogonal components in the parallel factor analysis model with simulations and applications to real-world data
ArticleAbstract: In this paper, we extend the use of disjoint orthogonal components to three-way table analysis withPalabras claves:Degeneracy, Disjoint components, heuristic algorithms, Parafac model, PCa, R Software, Three-way tablesAutores:Carlos Martin-Barreiro, John A. Ramirez-Figueroa, Leiva V., Martin-Casado A., Purificación Galindo-Villardón, Xavier CabezasFuentes:googlescopusA new algorithm for computing disjoint orthogonal components in the three-way tucker model
ArticleAbstract: One of the main drawbacks of the traditional methods for computing components in the three-way TuckePalabras claves:greedy algorithms, heuristic algorithms, PCa, R Software, SINGULAR VALUE DECOMPOSITION, Three-way tables, Tucker3 modelAutores:Carlos Martin-Barreiro, John A. Ramirez-Figueroa, Leiva V., Martin-Casado A., Nieto-Librero A.B., Purificación Galindo-VillardónFuentes:scopusA new approach to pbkp_redicting cryptocurrency returns based on the gold prices with support vector machines during the COVID-19 pandemic using sensor-related data
ArticleAbstract: In a real-world situation produced under COVID-19 scenarios, pbkp_redicting cryptocurrency returns aPalabras claves:Artificial Intelligence, data science, Digital currency, GOLD, Machine learning, SARS-COV-2, Sensing and data extractionAutores:Carlos Martin-Barreiro, Leiva V., Mahdi E., Mara’beh S.Fuentes:googlescopusA new birnbaum–saunders distribution and its mathematical features applied to bimodal real-world data from environment and medicine
ArticleAbstract: In this paper, we propose and derive a Birnbaum–Saunders distribution to model bimodal data. This nePalabras claves:Birnbaum–saunders distribution, data science, Estimation of moments and maximum likelihood, Monte Carlo method, Polynomial functions, Proportionate-effect law, R SoftwareAutores:Arrué J., Carlos Martin-Barreiro, Leiva V., Reyes J.Fuentes:googlescopusA new principal component analysis by particle swarm optimization with an environmental application for data science
ArticleAbstract: In this paper, we propose a new method for disjoint principal component analysis based on an intelliPalabras claves:Constrained binary particle swarm optimization, Data Mining, Disjoint principal components, Evolutionary computation, R Software, SINGULAR VALUE DECOMPOSITIONAutores:Carlos Martin-Barreiro, John A. Ramirez-Figueroa, Leiva V., Nieto-Librero A.B., Purificación Galindo-VillardónFuentes:scopusA two-stage location problem with order solved using a lagrangian algorithm and stochastic programming for a potential use in covid-19 vaccination based on sensor-related data
ArticleAbstract: Healthcare service centers must be sited in strategic locations that meet the immediate needs of patPalabras claves:heuristic algorithm, Lagrangian and semi-Lagrangian relaxations, Mathematical pro-gramming, SARS-COV2, Sensing and data extraction, Simple plant and uncapacitated facility location problems, XPRESS softwareAutores:Carlos Martin-Barreiro, Erwin J. Delgado, García S., Leiva V., Xavier CabezasFuentes:googlescopusDisjoint and functional principal component analysis for infected cases and deaths due to covid-19 in south american countries with sensor-related data
ArticleAbstract: In this paper, we group South American countries based on the number of infected cases and deaths duPalabras claves:data science, Disjoint and functional components, Infectious diseases, k-means clustering, Multivariate statistical methods, R Software, SARS-COV2, Sensing and data extractionAutores:Carlos Martin-Barreiro, John A. Ramirez-Figueroa, Leiva V., Purificación Galindo-Villardón, Xavier CabezasFuentes:googlescopusLot-size models with uncertain demand considering its skewness/kurtosis and stochastic programming applied to hospital pharmacy with sensor-related COVID-19 data
ArticleAbstract: Governments have been challenged to provide timely medical care to face the COVID-19 pandemic. UnderPalabras claves:GAMLSS methodology, Machine learning, Non-Gaussianity, SARS-COV2, Sensing and data extraction, statistical moments, Two-stage optimization algorithmsAutores:Carlos Martin-Barreiro, Huerta M., Leiva V., Rojas F.Fuentes:googlescopus