|
|
|
|
|
D. Criado-Ramón, L. G. B. Ruiz, J. R. S. Iruela and M. C. Pegalajar
This paper introduces the first completely unsupervised methodology for non-intrusive load monitoring that does not rely on any additional data, making it suitable for real-life applications. The methodology includes an algorithm to efficiently decompose...
ver más
|
|
|
|
|
|
|
|
|
|
|
D. Criado-Ramón, L. G. B. Ruiz and M. C. Pegalajar
Pattern sequence-based models are a type of forecasting algorithm that utilizes clustering and other techniques to produce easily interpretable predictions faster than traditional machine learning models. This research focuses on their application in ene...
ver más
|
|
|
|
|
|
|
|
|
|
|
M. C. Pegalajar, L. G. B. Ruiz, E. Pérez-Moreiras, J. Boada-Grau and M. J. Serrano-Fernandez
The goal of this study is to estimate the state of consciousness known as Flow, which is associated with an optimal experience and can indicate a person?s efficiency in both personal and professional settings. To predict Flow, we employ artificial intell...
ver más
|
|
|
|
|
|