Mostrando 5 resultados de: 5
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Subtipo de publicación
Conference Object(5)
Publisher
IEEE International Conference on Fuzzy Systems(2)
2021 IEEE Symposium Series on Computational Intelligence, SSCI 2021 - Proceedings(1)
Proceedings - 2021 International Conference on Computational Science and Computational Intelligence, CSCI 2021(1)
Proceedings - 2022 48th Latin American Computing Conference, CLEI 2022(1)
Área de conocimiento
Energía(4)
Aprendizaje automático(2)
Ciencias de la computación(1)
Minería de datos(1)
Origen
scopus(5)
Autonomous Cycle of Data Analysis Tasks for Scheduling the Use of Controllable Load Appliances using Renewable Energy
Conference ObjectAbstract: With the arrival of smart buildings with renewable energy generation capacities, new possibilities fPalabras claves:Artificial Intelligence, Data Analysis, energy consumption scheduling, Smart Buildings, smart gridsAutores:Giraldo J., Jaramillo A., José Lisandro Aguilar Castro, R-Moreno M.D., Zapata M., Zuluaga L.Fuentes:scopusAnalysis of Customer Energy Consumption Patterns using an Online Fuzzy Clustering Technique
Conference ObjectAbstract: Currently, there is a high rate of generation of new information about the Energy Consumption of cusPalabras claves:Clustering algorithm, fuzzy systems, LAMDA, ONLINE LEARNING, pattern evolutionAutores:Gull C.Q., José Lisandro Aguilar Castro, R-Moreno M.D., Viera J.Fuentes:scopusA Multi-label Approach for Diagnosis Problems in Energy Systems using LAMDA algorithm
Conference ObjectAbstract: In this paper, we propose a supervised multilabel algorithm called Learning Algorithm for MultivariaPalabras claves:diagnosis problems, fuzzy systems, LAMDA, Multilabel classificationAutores:Gull C.Q., José Lisandro Aguilar Castro, R-Moreno M.D.Fuentes:scopusA semi-supervised learning approach to study the energy consumption in smart buildings
Conference ObjectAbstract: In this work, we use the semi-supervised LAMDA-HSCC algorithm for characterizing the energy consumptPalabras claves:Energetic Consumption, LAMDA, Multivariate Data Analysis, semi-supervised learningAutores:Gull C.Q., José Lisandro Aguilar Castro, R-Moreno M.D.Fuentes:scopusA synthetic Data Generator for Smart Grids based on the Variational-Autoencoder Technique and Linked Data Paradigm
Conference ObjectAbstract: In a smart environment like the smart grids, it is necessary to have knowledge models that allow solPalabras claves:deep learning, Linked data, smart Grid, Synthetic Data Generator, Variational autoencodersAutores:José Lisandro Aguilar Castro, R-Moreno M.D., Santos R.D.Fuentes:scopus