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Hybrid intelligent supervision model of oil wells
Conference ObjectAbstract: In this work is presented a hybrid intelligent model based on Evolutionary Computation and Fuzzy SysPalabras claves:Autores:Camargo E., José Lisandro Aguilar CastroFuentes:scopusDeveloping a mathematical model of oil production in a well that uses an electric submersible pumping system
Conference ObjectAbstract: This paper presents an approach to get a mathematical model for describing the production of an ElecPalabras claves:Electro submersible pump efficiency, Genetic Programming, Identification problem, Well productionAutores:Camargo E., Jaramillo B., José Lisandro Aguilar Castro, Lozada H., María HalloFuentes:scopusA neo-fuzzy approach for bottom parameters estimation in oil wells
ArticleAbstract: In this work, an approach for the bottom parameters estimation in oil wells is presented. It is basePalabras claves:Artificial gas lift wells, Neofuzzy neurons, Neuro-fuzzy models, Oil system production, oil wells, Parameters estimationAutores:Aguilar-Martin J., Camargo E., Francklin Rivas, José Lisandro Aguilar Castro, Rios-Bolivar A.Fuentes:scopusA proposal for a cooperative cross-entropy method to tackle the unit commitment problem
ArticleAbstract: The paper presents a proposal about the Cooperative Cross-Entropy to solve Combinatorial OptimizatioPalabras claves:Combinatorial optimization problems, Cooperative cross-entropy, Unit commitment problemAutores:Amaya J.E., Camargo E., José Lisandro Aguilar Castro, Tarazona M.Fuentes:scopusAn approach for diagnosability analysis and sensor placement for continuous processes based on evolutionary algorithms and analytical redundancy
ArticleAbstract: In this work we propose to use an approach based on genetic algorithms to obtain analytical redundanPalabras claves:Bipartite graph, Diagnosability, Genetic Algorithm, Sensors placement, structural analysisAutores:Camargo E., J. Aguilar Castro, José Lisandro Aguilar Castro, Leal R., Rios-Bolivar A., Travé-Massuyès L.Fuentes:rraaescopusAn incremental learning approach to prediction models of SEIRD variables in the context of the COVID-19 pandemic
ArticleAbstract: Several works have proposed predictive models of the SEIRD (Susceptible, Exposed, Infected, RecoverePalabras claves:covid-19, Machine learning, pbkp_rediction modelAutores:Ardila D., Camargo E., Francklin Rivas, José Lisandro Aguilar Castro, Quintero Y.Fuentes:scopusAdvanced Supervision Of Oil Wells Based On Soft Computing Techniques
ArticleAbstract: In this work is presented a hybrid intelligent model of supervision based on Evolutionary ComputatioPalabras claves:Autores:Camargo E., José Lisandro Aguilar CastroFuentes:scopusApplicability of LAMDA as classification model in the oil production
ArticleAbstract: This work analyzes the utilization of classification models in the context of the oil industry and pPalabras claves:Classification Models, Data Mining, LAMDA, LAMDA-HAD, Oil businessAutores:Camargo E., José Lisandro Aguilar Castro, Lozada H., Luis Morales MoralesFuentes:scopusIntelligent Well Systems
Conference ObjectAbstract: In this paper is presented an Intelligent Well Systems for the Industrial Production of Oil. Such scPalabras claves:Artificial Intelligence, GAS LIFT, intelligente well systemsAutores:Aceros E., Camargo E., J. Aguilar Castro, José Lisandro Aguilar CastroFuentes:rraaescopusIntelligent supervision systems for improving the industrial production performance in oil wells
Conference ObjectAbstract: An Intelligent Supervision Scheme for the Industrial Production is presented in this work. Such schePalabras claves:Automation, Evolutionary computation, fuzzy logic, Gas lift wells, Neo-fuzzy systems, Nodal analysis, Supervision systemAutores:Aguilar-Martin J., Camargo E., Francklin Rivas, José Lisandro Aguilar Castro, Rios-Bolivar A.Fuentes:scopus