Comunicaciones y ponencias de congresos DEIO - EIOS Biltzarretako komunikazioak eta txostenak
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Publication Open Access Situación actual y prospectiva de futuro del sector de las energías renovables en Navarra(Gobierno de Navarra, Departamento de Economía y Hacienda, 2003) Pintor Borobia, Jesús María; García Ortega, Justo; Faulín Fajardo, Javier; Lera López, Fernando; Ingeniería Mecánica, Energética y de Materiales; Estadística e Investigación Operativa; Economía; Mekanika, Energetika eta Materialen Ingeniaritza; Estatistika eta Ikerketa Operatiboa; EkonomiaRazones económicas y medioambientales han hecho que la búsqueda de nuevas formas de energía se haya intensificado en los últimos años, desarrollándose distintos tipos de energías renovables. En el caso de la Unión Europea, se ha realizado una apuesta por este tipo de energías, produciéndose una especialización por países. La Comunidad Foral de Navarra es un claro ejemplo de esta sensibilidad, que le ha llevado a convertirse en un modelo de desarrollo. El presente trabajo recoge la situación actual de las energías renovables en la región, analizándolas desde el punto de vista de las empresas que realizan su actividad en este ámbito. Para ello, se ha determinado el conjunto de empresas que constituyen en Navarra el sector de las energías renovables, para a continuación proceder a analizarlo mediante una investigación de mercados. De este modo, se ha puesto de manifiesto las interrelaciones entre una política energética regional y la creación y desarrollo de un sector empresarial dinámico, competitivo y en crecimiento. El trabajo ofrece también una prospectiva de la situación para el período 2002-2005, contrastando los resultados obtenidos con distintos estudios nacionales y europeos.Publication Metadata only Búsqueda de submercados inmobiliarios mediante modelos de mixturas(Gobierno de Navarra, Departamento de Economía y Hacienda, 2003) Militino, Ana F.; Ugarte Martínez, María Dolores; Goicoa Mangado, Tomás; Estadística e Investigación Operativa; Estatistika eta Ikerketa OperatiboaLa heterogeneidad presente en el mercado inmobiliario dificulta enormemente su análisis y puede conllevar la presencia de submercados. En este caso, el modelo clásico de regresión lineal múltiple, ampliamente utilizado con este tipo de datos, puede no ser adecuado y, por tanto, es necesaria la utilización de técnicas estadísticas más específicas que resuelvan el problema de la heterogeneidad y de la búsqueda de submercados. En este trabajo se propone un modelo de mixturas de modelos lineales que proporciona un buen ajuste a los datos, a la vez que una clasificación de las observaciones en diferentes grupos o submercados potenciales. El modelo se ilustra mediante el análisis de un conjunto de 293 viviendas usadas de Pamplona.Publication Open Access Estimación del desempleo por comarcas en Navarra(Gobierno de Navarra, Departamento de Economía y Hacienda, 2005) Ugarte Martínez, María Dolores; Militino, Ana F.; González Ramajo, Begoña; Goicoa Mangado, Tomás; Sagaseta López, M.; Estadística e Investigación Operativa; Estatistika eta Ikerketa OperatiboaEl conocimiento del desempleo en una región es un indicador potente del ritmo de crecimiento de una economía, ya que de forma indirecta mide su capacidad para generar empleo. El Instituto de Estadística de Navarra está apostando por proporcionar en un futuro cercano estimaciones del desempleo a un nivel cada vez más desagregado. La heterogeneidad de las comarcas navarras y el interés mostrado por administraciones locales y sindicatos, hace necesario tener un conocimiento de la situación de desempleo a nivel comarcal, evitando así descansar únicamente en el resultado global para toda Navarra tal y como lo proporciona la Encuesta de Población Activa (EPA). La tarea es compleja, pero está incardinada además en uno de los objetivos prioritarios del proyecto europeo EURAREA, del cual ha formado parte el Instituto Nacional de Estadística (INE), y por ende, el Instituto de Estadística de Navarra. Es decir, hay un interés real en Europa por proporcionar estimaciones a nivel comarcal. En Navarra esta tarea ya ha comenzado y en este congreso presentamos algunos de los resultados obtenidos. En particular se ilustran las estimaciones preliminares derivadas de la aplicación de diversos estimadores basados en el diseño para obtener la proporción de parados por sexo en las siete comarcas de Navarra. Se compara además el comportamiento de diversos estimadores en términos del sesgo relativo y del error cuadrático medio relativo. Los estimadores ofrecidos permiten calcular además la estimación del número de ocupados e inactivos, así como de sus correspondientes tasas.Publication Open Access Exploring the limits of wind farm grouping for prediction error compensation(European Wind Energy Association, 2006) Gastón Romeo, Martín; Frías Paredes, Laura; Martí, Ignacio; Estadística e Investigación Operativa; Estatistika eta Ikerketa OperatiboaPublication Open Access Wind resources map of Spain at mesoscale: methodology and validation(European Wind Energy Association, 2008) Gastón Romeo, Martín; Pascal, Edurne; Frías Paredes, Laura; Martí, Ignacio; Irigoyen, Uxue; Cantero Nouqueret, Elena; Lozano, Sergio; Loureiro, Yolanda; Estadística e Investigación Operativa; Estatistika eta Ikerketa OperatiboaA wind resource map of Spain has been built using the mesoscale model Skiron. It covers all the Iberian geography. To measure the accuracy level of this map, a protocol of validation has been developed. It provides global information as well as reports about dierent regions, levels of wind speed, direction sector etc. A validation of the map using 50 meteorological stations is presented.Publication Open Access Wind resources map of Iberian Peninsula using a mesoscale model: comparison of different methodologies(European Wind Energy Association, 2009) Lozano, Sergio; Irigoyen, Uxue; Martí, Ignacio; Cantero Nouqueret, Elena; Pascal, Edurne; Fernandez, P.; Frías Paredes, Laura; Garciandia, J.; Zubillaga, E.; Estadística e Investigación Operativa; Estatistika eta Ikerketa OperatiboaWith an increasing number of wind farms planned in multiple locations without wind resource information, that comprise entire countries, there is a need for long term wind assessment, for both onshore and offshore wind resource potential. The focus of this work is to find the optimum methodology to build a wind map taking into account not only accuracy, but also the computational requirements. For this purpose six different wind resources maps have been calculated for Spain using a mesoscale model (SKIRON). The wind maps were calculated with different inputs and model configuration. An extensive validation was carried out using 24 meteorological station.Publication Open Access Support vector machines in the wind energy framework: a new model for wind energy forecasting(European Wind Energy Association, 2009) Frías Paredes, Laura; Pascal, Edurne; Irigoyen, Uxue; Cantero Nouqueret, Elena; Loureiro, Yolanda; Lozano, Sergio; Fernandes Correia, Pedro Miguel; Martí, Ignacio; Estadística, Informática y Matemáticas; Estatistika, Informatika eta MatematikaIn this work we expose a new model for wind energy forecasting based in Support Vector Machines. Support vector machines (SVMs) are a group of supervised learning methods that can be applied to classification or regression. They represent an extension to nonlinear models of the generalized portrait algorithm developed by Vladimir Vapnik. Support vector machines (SVMs) appeared in the early nineties as optimal margin classifiers in the context of Vapnik's statistical learning theory. Since then SVMs have been successfully applied to real-world data analysis problems, often providing improved results compared with other techniques. The SVMs operate within the framework of regularization theory by minimizing an empirical risk in a well-posed and consistent way. A clear advantage of the support vector approach is that sparse solutions to classification and regression problems are usually obtained: only a few samples are involved in the determination of the classification or regression functions. This fact facilitates the application of SVMs to problems that involve a large amount of data. Joint to that, the use of kernel functions into their algorithms allows the adaptability to nonlinear problems of SVMs. There are many "traditional" problems in the wind power forecasting systems that affect the accuracy and robustness of the forecasts, as availability of real power measures, the existence of wrong data and the nonlinearity of the relationship between meteorological variables and power. So, these robustness and adaptability of SVMs suggest that these types of learning machines could be a good set of tools to solve many problems in the wind energy context.Publication Open Access Breve análisis de la presentación de la Estadística en libros de texto(2013) Moler Cuiral, José AntonioPublication Open Access Wind power predictability assessment from large to local scale(European Wind Energy Association, 2013) Rodrigo, J.; Frías Paredes, Laura; Stoffels, Nicole; Bremen, Lueder von; Estadística, Informática y Matemáticas; Estatistika, Informatika eta MatematikaLarge wind power penetration and efficient wind farm operation require early consideration of the impact of wind power predictability from site to regional/country and continental levels. The aim of this work is to explore the added value of introducing wind power predictability in the wind resource assessment phase for large scale spatial planning and for wind farm performance evaluation. To this end, historical wind data are converted to virtual time series of wind power production on which forecasting models operate in hindcast mode to estimate predictability information. This information can be used to anticipate operational costs and lead to a better assessment of the cost-benefit of wind energy deployment. Numerical weather prediction models give us the opportunity to evaluate wind power predictability and other forecast skills. The COSMO-EU mesoscale model wind speed data is used to create a spatial dataset of different forecast skills and visualize those in form of European predictability maps at a resolution of 7×4 km. In addition to a large capacity factor, low wind variability is also desirable for smooth wind power integration. A smoothing factor determines the areas that benefit most from wind farm aggregation resulting in increased predictability and reduced variability. These forecast skill maps provide useful information for spatial planning and can be analyzed to determine the sources of forecasting errors, either by topographical effects or meteorological phenomena. At site level, wind measurements from a reference mast are converted into wind farm production time series making use of a microscale flow model. Then CENER's LocalPred wind power forecasting model is run, emulating operational conditions to assess predictability. A test case comprising two wind farms in Spain of different terrain complexity, equipped with measurements from the resource assessment and the operational phases, is presented to illustrate a methodology for local predictability assessment. Low wind power predictability is certainly a good indicator of quality-of-energy for grid integration. Hence, this type of information should be included during the development phase of a wind farm as complementary information about its performance. In conclusion, guidelines on how to produce and evaluate wind power predictability during the planning phase are provided in order to advise end-users on the use of these new layers of information.Publication Open Access Using biased randomization for trajectory optimization in robotic manipulators(Springer, 2016) Agustín Martín, Alba; Olivares, Alberto; Staffetti, Ernesto; Estadística e Investigación Operativa; Estatistika eta Ikerketa OperatiboaWe study the problem of optimization of trajectories for a robotic manipulator, with two degrees of freedom, which is constrained to pass through a set of waypoints in the workspace. The aim is to determine the optimal sequence of points and continuous optimal system trajectory. The actual formulation involves an optimal control problem of a dynamic system within integer variables that model the waypoints constrains. The nature of this problem, highly nonlinear and combinatorial, makes it particularly difficult to solve. The proposed method combines a meta-heuristic algorithm to determine the promising sequence of discrete points with a collocation technique to optimize the continuous path of the system. This method does not guarantee the global optimum, but can solve instances of dozens of points in reasonable computation time.Publication Open Access Optimizing airline crew scheduling using biased randomization: a case study(Springer, 2016) Agustín Martín, Alba; Gruler, Aljoscha; Armas, Jesica de; Juan, Ángel A.; Estadística e Investigación Operativa; Estatistika eta Ikerketa OperatiboaVarious complex decision making problems are related to airline planning. In the competitive airline industry, ecient crew scheduling is hereby of major practical importance. This paper presents a metaheuristic approach based on biased randomization to tackle the challenging Crew Pairing Problem (CPP). The objective of the CPP is the establishment of ight pairings allowing for cost minimizing crew- ight assignments. Experiments are done using a real-life case with dierent constraints. The results show that our easy-to-use and fast algorithm reduces overall crew ying times and the necessary number of accompanying crews compared to the pairings currently applied by the company.Publication Open Access A multicriteria analysis for the green VRP: a case discussion for the distribution problem of a Spanish retailer(Elsevier, 2017) Sawik, Bartosz; Faulín Fajardo, Javier; Pérez Bernabeu, Elena; Estadística e Investigación Operativa; Estatistika eta Ikerketa OperatiboaThis research presents the group of green vehicle routing problems with environmental costs translated into money versus production of noise, pollution and fuel consumption. This research is focused on multi-objective green logistics optimization. Optimality criteria are environmental costs: minimization of amount of money paid as externality cost for noise, pollution and costs of fuel versus minimization of noise, pollution and fuel consumption themselves. Some mixed integer programming formulations of multi-criteria vehicle routing problems have been considered. Mathematical models were formulated under assumption of existence of asymmetric distance-based costs and use of homogeneous fleet. The exact solution methods are applied for finding optimal solutions. The software used to solve these models is the CPLEX solver with AMPL programming language. The researchers were able to use real data from a Spanish company of groceries. Problems deal with green logistics for routes crossing the Spanish regions of Navarre, Basque Country and La Rioja. Analyses of obtained results could help logistics managers to lead the initiative in area of green logistics by saving money paid for environmental costs as well as direct cost of fuel and minimization of pollution and noise.Publication Open Access Implementation of artificial intelligence algorithms in climatic zoning according with energy demand in dwellings. A european case(2021) Llorente Yoldi, Javier; Gastón Romeo, Martín; Frías Paredes, Laura; Ur Rehman, Hassam; Estadística e Investigación Operativa; Institute of Smart Cities - ISC; Estatistika eta Ikerketa OperatiboaScience has shown, based on data and knowledge, that there is clear evidence that global warming is not a transient effect, and that it is caused mainly by human activity. The consequences of climate change can be noted and quantified nowadays, but the worst thing is that these impacts are expected to intensify in the coming decades. Obviously, global problems require global solutions, and even if there are certain difficulties to define a clear path, there is no doubt that the worldwide efforts should lead to keep the global temperatura increase to well below 1.5ºCPublication Open Access TOUCHLESS: demonstrations of contactless haptics for affective touch(ACM, 2023) Chew, Sean; Dalsgaard, Tor-Salve; Maunsbach, Martin; Bergström, Joanna; Seifi, Hasti; Hornbæk, Kasper; Irisarri Erviti, Josu; Ezcurdia Aguirre, Íñigo Fermín; Iriarte Cárdenas, Naroa; Marzo Pérez, Asier; Frier, William; Georgiou, Orestis; Sheremetieva, Anna; Kwarciak, Kamil; Stroiński, Maciej; Hemmerling, Daria; Maksymenko, Mykola; Cataldo, Antonio; Obrist, Marianna; Haggard, Patrick; Subramanian, Sriram; Estadística, Informática y Matemáticas; Estatistika, Informatika eta MatematikaA set of demonstrators of contactless haptic principles is described in this work. The technologies are based on electrostatic piloerection, chemical compounds and ultrasound. Additionally, applications related to affective touch are presented, ranging from storytelling to biosignal transfer, accompanied with a simple application to edit dynamic tactile patterns in an easy way. The demonstrators are the result of the Touchless project, which is a H2020 european collaborative project that integrates 3 universities and 3 companies. These demostrators are contactless haptic experiences and thus facilitate the come-and-interact paradigm, where users can approach the demo booth and directly experience the applications without having to wear devices, making the experience fast and hygienic.