Application of genetic algorithms for the calibration of an air quality model and its validation using pollutant measures from the surroundings of an electric power plant

[EN]This work presents the calibration and validation of an air quality finite element model applied to emissions from a thermal power plant located in Gran Canaria. The calibration is performed using genetic algorithms. To calibrate and validate the model, the authors use empirical measures of pollutants concentrations from 4 stations located nearby the power plant; an hourly record per station during 3 days is available. Measures from 3 stations will be used to calibrate, while validation will use measures from the remaining station…

Contributions to underwater glider path planning

[ES] La Planificación de Rutas o Caminos es un disciplina de Robótica que trata la búsqueda de caminos factibles u óptimos. Para la mayoría de vehículos y entornos, no es un problema trivial y por tanto nos encontramos con un gran diversidad de algoritmos para resolverlo, no sólo en Robótica e Inteligencia Artificial, sino también como parte de la literatura de Optimización, con Métodos Numéricos y Algoritmos Bio-inspirados, como Algoritmos Genéticos y el Algoritmo de la Colonia de Hormigas. El caso particular de escenarios de costes variables es considerablemente difícil de abordar porque el entorno en el que se mueve el vehículo cambia con el tiempo. El presente trabajo de tesis estudia este problema y propone varias soluciones prácticas para aplicaciones de Robótica Submarina.

Wind ensamble forecasting using an adaptive mass-consistent model

[EN]Ensemble forecasting [1] is a methodology to deal with uncertainties in the numerical wind prediction. In this work we propose to apply ensemble methods to the adaptive wind forecasting model presented in [2]. The wind _eld forecasting is based on a mass-consistent model and a log-linear wind pro_le using as input data the resulting forecast wind from Harmonie [3], a Non-Hydrostatic Dynamic model. The mass-consistent model parameters are estimated by using genetic algorithms [4]. The mesh is generated using the meccano method [5] and adapted to the geometry. The main source of uncertainties in this model is the parameter estimation and the in- trinsic uncertainties of the Harmonie Model…

Ensemble wind forecasting based on the HARMONIE model and adaptive finite elements in complex orography

[EN]Ensemble forecasting is a methodology to deal with uncertainties in the numerical wind prediction. In this work we propose to apply ensemble methods to the adaptive wind forecasting model presented in. The wind field forecasting is based on a mass-consistent model and a log-linear wind profile using as input data the resulting forecast wind from Harmonie, a Non-Hydrostatic Dynamic model used experimentally at AEMET with promising results. The mass-consistent model parameters are estimated by using genetic algorithms. The mesh is generated using the meccano method and adapted to the geometry…