Global and Local Clustering-Based Regression Models to Forecast Power Consumption in Buildings

The study of energy efficiency in buildings is an active field of research. Modeling and predicting energy related magnitudes leads to analyze electric power consumption and can achieve economical benefits. In this study, classical time series analysis and machine learning techniques, introducing clustering in some models, are applied to predict active power in buildings. The real data acquired corresponds to time, environmental and electrical data of 30 buildings belonging to the University of León (Spain). Firstly, we segmented buildings in terms of their energy consumption using principal component analysis. Afterwards, we applied state of the art machine learning methods and compare bet…

Ciberseguridad : el reto del siglo XXI

El siglo XXI es el siglo del dato, su análisis y de la conectividad; en definitiva, el siglo de la información en tiempo real y disponible para cualquiera en cualquier lugar del mundo. Dichos datos están impactando en todos los ámbitos de la sociedad y de la economía de tal forma que no se entiende ningún sector productivo ni ninguna relación social sin dato; todos tenemos algún lugar en las redes sociales desde donde intercambiamos experiencias personales o profesionales. Si a este hecho se le suma el auge de la Inteligencia Artificial, se tiene un siglo en el que los avances tecnológicos van a ser totalmente disruptivos para todos nosotros.

Machine learning methods to forecast temperature in buildings

Efficient management of energy in buildings saves a very important amount of resources (both economic and technological). As a consequence, there is a very active research in this field. One of the keys of energy management is the prediction of the variables that directly affect building energy consumption and personal comfort. Among these variables, one can highlight the temperature in each room of a building. In this work we apply different machine learning techniques along with other classical ones for predicting the temperatures in different rooms. The obtained results demonstrate the validity of these techniques for predicting temperatures and, therefore, for the establishment of optim…

Forecasting Techniques for Energy Optimization in Buildings

Development and validation of the Migraine Screen Questionnaire (MS-Q).

Aim.—To develop and evaluate the clinimetric properties of a new migraine screening questionnaire: the Migraine Screen Questionnaire (MS-Q). Background.—Migraine is a public health problem requiring screening programs and tools to ensure early detection. Methods.—A questionnaire was developed based on the criteria of the International Headache Society (IHS) and a review of the literature by a committee of experts. Stage I: The original version of the MS-Q was distributed by mail and completed by Pfizer employees and self-administered to neurological patients; all subjects were afterward evaluated by a neurologist who was blinded to the MS-Q results, to establish an independent IHS diagnosis…