Mostrando 10 resultados de: 17
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Universidad Laica VICENTE ROCAFUERTE de Guayaquil(5)
International Journal of Renewable Energy Research(2)
Energy Procedia(1)
Neural Computing and Applications(1)
Proceedings - 2022 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2022(1)
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Física aplicada(13)
Economía de la tierra y la energía(10)
Ciencias de la computación(4)
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Aprendizaje automático(2)
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Comparisons of Deep Learning Models to predict Energy Consumption of an Educational Building
Conference ObjectAbstract: According to the latest United Nations Environment Programme report, in 2020, the construction and oPalabras claves:Artificial Neural Network, deep learning, energy consumption forecasting, GRU, LSTM, MLPAutores:Eduardo Flores-Morán, Franklin Ricardo Parrales Bravo, Julio Barzola-Monteses, Wendy Yánez-PazmiñoFuentes:googlescopusAnalisis del Potencial de Energìa Eòlica a partir de mediciones in situ en Atahualpa
ArticleAbstract: En Ecuador, durante los últimos 10 años se ha iniciado la exploración y aprovechamiento de recursosPalabras claves:Autores:Ángel Valencia, Ángelo Vera, Carlos Briones, Fausto Cabrera, Julio Barzola-Monteses, Mayken EspinozaFuentes:rraaeAnalysis of hybrid solar/wind/diesel renewable energy system for off-grid rural electrification
ArticleAbstract: Due to the rising energy demand and even the lack of coverage of the supplied energy to the total poPalabras claves:Feasibility analysis, Homer, Hybrid electric system, renewable energiesAutores:Cabrera F., Julio Barzola-Monteses, Mayken Espinoza-AndaluzFuentes:googlescopusAn Initial Approach About Data Preprocessing Techniques Applied to Polymer Electrolyte Fuel Cells: A Case Study
Conference ObjectAbstract: Like other fields, a great amount of data is present when a polymer fuel cell is analyzed. Several vPalabras claves:EDA, Fuel Cell, Machine learning, PreprocessingAutores:Ester Melo, James Peñafiel, Julio Barzola-Monteses, Mayken Espinoza-AndaluzFuentes:googlescopusApplied LSTM Neural Network Time Series to Forecast Household Energy Consumption
Conference ObjectAbstract: In Ecuador, energy consumption is accentuated in the residential sector due to population growth andPalabras claves:buildings, Energy efficiency, forecasting, LSTM, TIME SERIESAutores:Génesis Segura, José Guamán, Julio Barzola-Monteses, Mónica Mite-León, Vicente Macas-EspinosaFuentes:googlescopusApplied 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:rraaeAnálisis de técnicas de validación en modelos aprendizaje automático aplicadas en series tiempo de variable energéticas de un edificio universitario.
Bachelor ThesisAbstract: El ahorro de energía o reducción del consumo de energía es la forma más fácil y efectiva de reducirPalabras claves:Consumo energético, Cross validation, Energy consumption, Machine Learning supervisado, RF, SERIES DE TIEMPO, Supervised machine learning, SVR, TIME SERIES, validación cruzada, XGBoostAutores:John Andrés Robles García, Julio Barzola-MontesesFuentes:rraaeAnálisis técnico y financiero de grid parity residencial con fuente de energía solar
ArticleAbstract: Ecuador, debido a su ubicación geográfica, cuenta con irradiación solar de adecuada intensidad y durPalabras claves:Autores:Julio Barzola-Monteses, Luca RubiniFuentes:rraaeHydropower production prediction 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:googlescopusEnsemble Learning Models Applied in Energy Time Series of a University Building
Conference ObjectAbstract: During 2020, the construction and operation of buildings globally accounted for more than a third (3Palabras claves:Cross-validation for time series, Decision Trees, Energy consumption, ensemble learning, Extreme Gradient Boosting, random forestAutores:Isaakc Ortiz-Aguirre, Julio Barzola-Monteses, Mayken Espinoza-AndaluzFuentes:googlescopus