9 documents found, page 1 of 1
A deep learning-based model to predict nitrogen dioxide in urban environments
Oliveira, P.; Díaz-Longueira, Antonio; Marcondes, Francisco Supino; Durães, Dalila; Calvo-Rolle, José Luis; Jove, Esteban; Novais, PauloNowadays, our society faces several problems regarding the environmental sustainability of our planet. One of these problems, which severely impacts human lives, such as climate change, is air pollution. Air pollution in urban environments is derived from road transport and different economic activities and directly impacts human health. Then, air quality monitoring stations are essential to determine potential...
Geothermal heat exchanger’s temperature input sensor prediction based on deep l...
Oliveira, P.; Arcano-Bea, Paula; Marcondes, Franciso S.; Calvo-Rolle, José Luis; Novais, Paulo; Jove, EstebanThe goal of this study was to test many models in order to check which one better predicted the heat exchanger of a bioclimatic building. A number of regression models, pre-processing methods, and data analyses are compared in the study to forecast the input collector temperature of the heat pump. Specifically, three different techniques have been considered in this research work: Multilayer Perceptrons, Long S...
A novel method for anomaly detection using beta hebbian learning and principal ...
Zayas-Gato, Francisco; Michelena, Álvaro; Quintián, Héctor; Jove, Esteban; Casteleiro-Roca, José-Luis; Leitão, Paulo; Calvo-Rolle, Jose LuisIn this research work a novel two-step system for anomaly detection is presented and tested over several real datasets. In the first step the novel Exploratory Projection Pursuit, Beta Hebbian Learning algorithm, is applied over each dataset, either to reduce the dimensionality of the original dataset or to face nonlinear datasets by generating a new subspace of the original dataset with lower, or even higher, ...
A novel intelligent approach for man-in-the-middle attacks detection over inter...
Michelena, Álvaro; Aveleira-Mata, José; Jove, Esteban; Bayón-Gutiérrez, Martín; Novais, Paulo; Fontenla Romero, Oscar; Calvo-Rolle, José LuisOne of the most common attacks is man-in-the-middle (MitM) which, due to its complex behaviour, is difficult to detect by traditional cyber-attack detection systems. MitM attacks on internet of things systems take advantage of special features of the protocols and cause system disruptions, making them invisible to legitimate elements. In this work, an intrusion detection system (IDS), where intelligent models c...
A distributed topology for identifying anomalies in an industrial environment
Zayas-Gato, Francisco; Michelena, Alvaro; Jove, Esteban; Casteleiro-Roca, Jose-Luis; Quintian, Hector; Novais, Paulo; Albino Mendez-Perez, JuanThe devastating consequences of climate change have resulted in the promotion of clean energies, being the wind energy the one with greater potential. This technology has been developed in recent years following different strategic plans, playing special attention to wind generation. In this sense, the use of bicomponent materials in wind generator blades and housings is a widely spread procedure. However, the ...
An intelligent system for harmonic distortions detection in wind generator powe...
Jove, Esteban; González-Cava, Jose Manuel; Casteleiro-Roca, José-Luis; Alaiz-Moretón, Héctor; Baruque, Bruno; Leitão, Paulo; Méndez Pérez, Juan AlbinoThe high concern about climate change has boosted the promotion of renewable energy systems, being the wind power one of the key generation possibilities in this field. In this context, with the aim of ensuring the energy efficiency, the present work deals with the fault detection in the power electronic circuits of a wind generator system placed in a bioclimatic house. To do so, different outliers that emulate...
A comparative study to detect flowmeter deviations using one-class classifiers
Jove, Esteban; Casteleiro-Roca, José Luis; Quintián, Héctor; Zayas-Gato, Francisco; Novais, Paulo; Méndez-Pérez, Juan Albino; Calvo-Rolle, José LuisThe use of bicomponent materials has encouraged the proliferation of wind turbine blades to produce electric power. However, the high complexity of the process followed to obtain this kind of materials difficult the problem of detecting anomalous situations in the plant, due to sensors or actuators malfunctions. This work analyses the use of different one-class techniques to detect deviations in one flowmeter l...
Solar Thermal Collector Output Temperature Prediction by Hybrid Intelligent Mod...
Casteleiro-Roca, José-Luis; Chamoso, Pablo; Jove, Esteban; González-Briones, Alfonso; Quintián, Héctor; Fernández-Ibáñez, María-IsabelCurrently, there is great interest in reducing the consumption of fossil fuels (and other non-renewable energy sources) in order to preserve the environment; smart buildings are commonly proposed for this purpose as they are capable of producing their own energy and using it optimally. However, at times, solar energy is not able to supply the energy demand fully; it is mandatory to know the quantity of energy n...
Bioinspired hybrid model to predict the hydrogen inlet fuel cell flow change of...
Alaiz-Moretón, Héctor; Jove, Esteban; Casteleiro-Roca, José-Luis; Quintián, Héctor; López García, Hilario; Benítez-Andrades, José Alberto; Novais, PauloThe present research work deals with prediction of hydrogen consumption of a fuel cell in an energy storage system. Due to the fact that these kind of systems have a very nonlinear behaviour, the use of traditional techniques based on parametric models and other more sophisticated techniques such as soft computing methods, seems not to be accurate enough to generate good models of the system under study. Due to...