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Antonio Sánchez-Esguevillas
Researcher at University of Valladolid
Publications - 55
Citations - 2826
Antonio Sánchez-Esguevillas is an academic researcher from University of Valladolid. The author has contributed to research in topics: Smart grid & The Internet. The author has an hindex of 21, co-authored 52 publications receiving 1968 citations. Previous affiliations of Antonio Sánchez-Esguevillas include Telefónica & Washington State University.
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Network Traffic Classifier With Convolutional and Recurrent Neural Networks for Internet of Things
TL;DR: A new technique for NTC based on a combination of deep learning models that can be used for IoT traffic provides better detection results than alternative algorithms without requiring any feature engineering, which is usual when applying other models.
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A Survey on Electric Power Demand Forecasting: Future Trends in Smart Grids, Microgrids and Smart Buildings
Luis Hernandez,Carlos Baladrón,Javier M. Aguiar,Belen Carro,Antonio Sánchez-Esguevillas,Jaime Lloret,Joaquim Massana +6 more
TL;DR: This review discusses the most relevant studies on electric demand prediction over the last 40 years, and presents the different models used as well as the future trends, and analyzes the latest studies on demand forecasting in the future environments that emerge from the usage of smart grids.
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Conditional Variational Autoencoder for Prediction and Feature Recovery Applied to Intrusion Detection in IoT.
TL;DR: This work is unique in the network intrusion detection field, presenting the first application of a conditional variational autoencoder and providing the first algorithm to perform feature recovery.
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Application of deep reinforcement learning to intrusion detection for supervised problems
TL;DR: This work presents a novel application of several deep reinforcement learning (DRL) algorithms to intrusion detection using a labeled dataset, and shows that DRL can improve the results of intrusion detection in comparison with current machine learning techniques.
Journal ArticleDOI
A multi-agent system architecture for smart grid management and forecasting of energy demand in virtual power plants
Luis Hernandez,Carlos Baladrón,Javier M. Aguiar,Belen Carro,Antonio Sánchez-Esguevillas,Jaime Lloret,David Chinarro,Jorge J. Gómez-Sanz,Diane J. Cook +8 more
TL;DR: This article presents a multi-agent system model for virtual power plants, a new power plant concept in which generation no longer occurs in big installations, but is the result of the cooperation of smaller and more intelligent elements.