Mostrando 6 resultados de: 6
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Publisher
2020 IEEE ANDESCON, ANDESCON 2020(1)
Communications in Computer and Information Science(1)
Neural Computing and Applications(1)
Proceedings - International Conference of the Chilean Computer Science Society, SCCC(1)
SCOPUS(1)
Área temáticas
Física aplicada(3)
Ciencias de la computación(1)
Economía de la tierra y la energía(1)
Enfermedades(1)
Medicina y salud(1)
Applied LSTM neural network time series to forecast household energy consumption
ArticleAbstract: In Ecuador, energy consumption is accentuated in the residential sector due to population growth anPalabras claves:buildings, Energy efficiency, forecasting, LSTM, TIME SERIESAutores:Génesis Segura, José Guamán, Julio Barzola-Monteses, Mónica Mite-León, Vicente Macas-EspinosaFuentes:rraaeDesarrollo de modelo pbkp_redictivo basado en algoritmos de aprendizaje supervisado de Machine Learning, para el análisis de datos en pacientes con la enfermedad de Crohn.
Bachelor ThesisAbstract: La enfermedad de Crohn es determinada como preocupación a nivel mundial que como efecto puede ocasioPalabras claves:Árbol de Clasificación, classification tree, Crohn's disease, Enfermedad de Crohn, FACTORES DE RIESGO, Gradient Boosting Classification, Machine Learning, ,METODOLOGÍA XP, RISK FACTORS, XP MethodologyAutores:Elena de los Angeles Bajaña Diaz, Julio Barzola-Monteses, Rogelio David Loja YagualFuentes:rraaeForecasting Energy Consumption in Residential Department Using Convolutional Neural Networks
Conference ObjectAbstract: During 2017, the construction and operation of buildings worldwide represented more than a third (36Palabras claves:buildings, cnn, CNN-LSTM, ConvLSTM, Energy efficiency, Pbkp_rediction models, TIME SERIESAutores:Franklin Ricardo Parrales Bravo, Julio Barzola-Monteses, Marcos Guerrero, Mayken Espinoza-AndaluzFuentes:scopusEnergy Consumption of a Building by using Long Short-Term Memory Network: A Forecasting Study
Conference ObjectAbstract: Buildings have a dominant presence in energy consumption for the transition to clean energy. DuringPalabras claves:electric load time series, energy efficiency building, Feed-forward neural networks, long short-Term memoryAutores:Eduardo Flores-Morán, Julio Barzola-Monteses, Mayken Espinoza-Andaluz, Mónica Mite-LeónFuentes:googlescopusHydropower production pbkp_rediction using artificial neural networks: an Ecuadorian application case
ArticleAbstract: Hydropower is among the most efficient technologies to produce renewable electrical energy. HydropowPalabras claves:Artificial Neural Network, Hydropower production forecasting, LSTM, MLP, Monthly electricity production, Sequence to sequenceAutores:Fajardo W., Gómez-Romero J., Julio Barzola-Monteses, Mayken Espinoza-AndaluzFuentes:googlescopusParticle Swarm Optimization and Genetic Algorithm PID for DC motor position controllers
Conference ObjectAbstract: Due to the increasing number of applications, researchers have developed several methodologies to coPalabras claves:Genetic Algorithm, Particle Swarm Optimization, PID ControllerAutores:Eduardo Flores-Morán, Ivette Carrera-Manosalvas, Julio Barzola-Monteses, Luis Arturo Espín Pazmiño, Luis Espin-Pazmiño, Wendy Yánez-PazmiñoFuentes:googlescopus