editor imat

Numerical simulation for chemorepulsive and productive models

Abstract: Chemotaxis is understood as the biological process of the movement of living organisms in response to a chemical stimulus which can be given towards a higher (attractive) or lower (repulsive) concentration of a chemical substance. At the same time, the presence of living organisms can produce or consume chemical substance.   We have studied the …

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Opinion formation Models: from individual interactions to the asymptotic behaviour of the whole population

Abstract: Agent based models are of special interest for interdisciplinary collaboration with specialists on the field, since they allow to consider specifically which are the features of the interactions behind the processes, when drawing the (discrete) master equations.   Mean field equations could be derived (e.g. at cellular level), taking into account diverse heterogeneities of the agents …

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Machine Learning for a Renewable European Energy System

Abstract: We propose a novel time-period clustering methodology that maintain chronology of input data to make more efficient investment decisions in renewable generation. Read more Researchers: Juan Miguel Morales, Salvador Pineda Morente Related project: PowerMath: Mathematical Methods for Data-driven Power Systems iMAT research line: RL1. Modeling of Energy Systems

Integration of large-scale heat pumps in the district heating systems of Greater Copenhagen

Abstract: Analysis of the technical and private economic aspects of integrating a large capacity of electric-driven heat pumps in the district heating system of Greater Copenhagen, which a full-fledged district heating system with many consumers and suppliers. Read more Researchers: Juan Miguel Morales, Bjarne Bach, Jesper Werling, Torben Ommen, Marie Münster, Brian Elmegaard Partner: EA …

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Modeling of light pollution due to urban lighting networks by Machine Learning techniques

Abstract: The project dealt with the elaboration of a mathematical algorithm for prediction of the light pollution as a function of the characteristics of the urban environment and lighting.  The company IMESAPI provided real measurements of light pollution in cities. Several Machine learning techniques were used to approximate the light pollution, determining the most appropriate …

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Modeling of chlorination concentration in public fountains by Machine Learning techniques

Abstract: The project dealt with the elaboration of a mathematical algorithm for prediction of the chlorine concentration in ornamental public fountains. The purpose was to optimize the life of pipes and fountain mechanisms while keeping safe levels of water chlorination. IMESAPI provided real measurements of chorination data. Several Machine learning techniques were used to approximate …

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Modeling of the electric perturbations in urban lighting networks by Machine Learning techniques

Abstract: The project dealt with the elaboration of a mathematical algorithm for prediction of the perturbation generated in the electric currents in urban lighting networks by regulation devices.  These regulators are used to diminish the light intensity at late night hours. However, the theoretical savings in electric energy are limited by the electric perturbations produced …

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