Ameva: An autonomous discretization algorithm

This paper describes a new discretization algorithm, called Ameva, which is designed to work with supervised learning algorithms. Ameva maximizes a contingency coefficient based on Chi-square statistics and generates a potentially minimal number of discrete intervals. Its most important advantage, in contrast with several existing discretization algorithms, is that it does not need the user to indicate the number of intervals. We have compared Ameva with one of the most relevant discretization algorithms, CAIM. Tests performed comparing these two algorithms show that discrete attributes generated by the Ameva algorithm always have the lowest number of intervals, and even if the number of classes is high, the same computational complexity is maintained. A comparison between the Ameva and the genetic algorithm approaches has been also realized and there are very small differences between these iterative and combinatorial approaches, except when considering the execution time.Ministerio de Educación y Ciencia TSI2006-13390-C02-02Junta de Andalucía P06-TIC-0214

¿Where do we go? OnTheWay: A prediction system for spatial locations

Ponencia presentada en: I International Conference on Ubiquitous Computing. Alcalá de Henares, Madrid, Spain, June 7-9, 2006In ubiquitous computing we need to know the present context in order to interact properly with the nearby smart elements. When we are moving outdoors, mobile devices take a very important role because they provide us with a link between the world outside and ourselves through means of intelligent interfaces. There are a lot of situations in which it would be very useful to know or foresee the future context, i.e. as a geographic environment, in which we could find ourselves in a near future, and at the same time being able to use that information from our devices. Therefore we must preview this location with enough precision and time and be able to use this information from our mobile device. In our “OnTheWay” system, we used GPS technology and databases made of past paths taken by a person, in order to predict the next location, once we had begun a new course, comparing the new one with those ones stored. The results were amazing: from the data collected about paths travelled during a month and five days, we got the actual destination in 98% of cases, when we have only made a 30,35% of the total path. Therefore, including statistic and semantic information will allow us to upgrade our results, due to the sedentary human behaviour, the small number of frequently visited locations and the fact that the paths used to arrive to these locations are usually the sam

Qualitative Comparison of Temporal Series. QSI

In this paper, the study of systems that evolve in time by means of the comparison of time series is proposed. An improvement in the form to compare temporal series with the incorporation of qualitative knowledge by means of qualitative labels is carried out. Each label represents a rank of values that, from a qualitative perspective, may be considered similar. The selection of labels of a single character allows the application of algorithms of string comparison. Finally, an index of similarity of time series based on the similarity of the obtained strings is defined.Comisión Interministerial de Ciencia y Tecnología DPI2001-4404-EComisión Interministerial de Ciencia y Tecnología DPI2000-0666-C02-0

Algoritmo para la caracterización univoca de metamateriales basados en inclusiones quirales

Electromagnetic characterization is perfomed from the reflection and transmission coefficients by making use of retrieval algorithms. However, it is known the existence of uncertainties in the determination of these electromagnetic parameters. Here, we present a new algorithm that uses some techniques in order to avoid these uncertainities, some based on continuity conditions of physical magnitudes and some others based on causality relations, that is, exploiting Kramers-Kronig relations.Ingeniería, Industria y Construcció

Análisis energético-económico de instalaciones fotovoltaicas de autoconsumo con batería

La reciente apuesta por el uso de energías renovables ha llevado a un aumento de las instalaciones de autoconsumo en las viviendas europeas. Esto conlleva una inversión en la que influye directamente el modelo de precios del país en el que se encuentre la instalación, obteniendo generalmente mayor rentabilidad a mayores precios de la electricidad. En este trabajo se ha elaborado un modelo que permite obtener la rentabilidad de una inversión para el caso de una instalación fotovoltaica con baterías. Se muestran resultados obtenidos a partir de datos de entrada relacionados con el clima, la dimensión de la instalación tanto en potencia fotovoltaica instalada como en almacenamiento y datos económicos de precios de la electricidad. Se ha hecho el análisis sobre una instalación “tipo”, con unos parámetros energéticos y de costes dados, con el fin de observar la influencia de los precios eléctricos. Para profundizar, se variarán las dimensiones de la instalación y se tendrá en cuenta el efecto de degradación de las baterías, una variable fundamental en una inversión a largo plazo. En cuanto a los términos económicos, se plantearán cuatro escenarios hipotéticos de precios en los mercados eléctricos de España y Alemania.Recent push for renewable energy use has led to an increase of photovoltaic (PV) self-consumption facilities in European households. This needs an investment that depends on the state’s system of electricity prices, achieving more profitability as electricity prices rise. This project consists of a model that is able to obtain the profitability of an investment for a self-consumption PV system with batteries. Results shown based on input data related with climate, installed PV power, battery size and economic data as electricity prices. The analysis has been made selecting a typical day, whose energy values as load demand profile or solar radiation, will repeat over the year. System costs will also be given, so the results focus on the electricity prices influence. To go further, several system sizes will be studied taking the degradation phenomena into account, a major parameter when analysing long-time investments. Regarding economic factors, four hypothetical electricity price scenarios will be held, using Spain and Germany electricity markets.Universidad de Sevilla. Grado en Ingeniería de Tecnologías Industriales

Índice para la comparación cualitativa de series temporales

Las series temporales son conjuntos de datos complejos de una gran importancia. Aparecen en aplicaciones científicas, financieras, biológicas, estadísticas, , y como ejemplos de éstas se incluyen índices de precios de acciones, volúmenes de ventas de un producto, datos en telecomunicaciones, señales médicas unidimensionales o sucesiones de me didas medioambientales. Esta pequeña enumeración demuestra que en cualquier campo de aplicación se utilizan series temporales. Si bien el concepto de serie temporal, como un conjunto de valores para los que tiene relevancia el momento temporal en que cada uno de ellos ha sido registrado, es muy simple y todo el mundo puede recordar múltiples ejemplos prácticos, el tratamiento automatizado de estos datos presenta innumerables problemas. Este proyecto de tesis se centra en el problema de la comparación de series con la intención de proporcionar mecanismos que, haciendo uso de características cualitativas, permitan identificar el grado de parecido o similitud entre series. El estudio de los sistemas que evolucionan en el tiempo es un área de investigación muy actual y cómo puede entenderse fácilmente, la evolución de cualquier variable de uno de estos sistemas genera de forma directa una serie temporal. Una seria temporal contiene, en su versión más simple, una secuencia de número reales, cada número representado el valor de una magnitud en un instante de tiempo. Normalmente, estas series son almacenadas en bases de datos y es necesario desarrollar algoritmos para su análisis con la intención de poder extraer conocimiento de la infancia almacenada. El primer problema para el tratamiento de esa información viene dado por la dimensión de las bases de datos generadas que presentan tamaños que hacen complicado un procesamiento eficiente. Por otro lado puede considerarse que una serie temporal es un objeto complejo almacenado en la base de datos, siendo necesaria la definición de algoritmos que permita operar con estos objetos complejos de una forma imposible de abarcar con los algoritmos clásicos diseñados para bases de datos relacionados. Dentro de esta problemática de la manipulación de los datos almacenados el hecho de cuantificar el grado de similitud o disimilitud entre objetos es un tema de gran trascendencia para muchas aplicaciones de minería de datos, aprendizaje automático, Sin embargo, para estos objetos complejos ni la definición de qué se entiende por similitud es en ningún modo evidente y única. Una posibilidad poco utilizada hasta el momento es explotar la información obtenida desde un punto de vista cualitativo. La idea radica en abstraer la información puramente numérica por medio de la definición de características cualitativas que la representen

QSI - Alternative Labelling and Noise Sensitivity

The are different approaches to the temporal study of time evolving systems. In the paper, this study is carried out by means of the comparison of the time series. This paper continues previous Works on QSI and studies the noise sensitivity of this index. The noise sensitivity dependes basically on the labelling process. This study is completed with a comparison with other posible labelling. The alternative labelling tecniques are selected kkeping different goals in mind: A better represntativeness of the class marks, a reduced moise sensivity and a similar number of every symbol into which yhe series are translated. We have carried out a detailed study applying different leveles of noise for all this labeling schemes and checking the quality of the obtaines index.Comité Interministerial de Ciencia y Tecnología DPI2001-4404-EJunta de Andalucía ACC-265-TIC-200

OnTheWay : a prediction system for spatial locations

In ubiquitous computing we need to know the present context in order to interact properly with the nearby smart elements. When we are moving outdoors, mobile devices take a very important role because they provide us with a link between the world outside and ourselves through means of intelligent interfaces. There are a lot of situations in which it would be very useful to know or foresee the future context, i.e. as a geographic environment, where we could find ourselves in a near future, and at the same time being able to use that information from our devices. Therefore we must preview this location with enough precision and time and be able to use this information from our mobile device. In our “OnTheWay” system, we used GPS technology and databases made of past paths taken by a person, in order to predict the next location, once we had begun a new course, comparing the new one with those ones stored. The results were amazing: from the data collected about paths travelled during a month and five days, we got the actual destination in 98% of cases, when we have only made a 30,35% of the total path. Therefore, including statistic and semantic information will allow us to upgrade our results, due to the sedentary human behaviour, the small number of frequently visited locations and the fact that the paths used to arrive to these locations are usually the same

A new approach to qualitative learning in time series

In this paper the k-nearest-neighbours (KNN) based method is presented for the classification of time series which use qualitative learning to identify similarities using kernels. To this end, time series are transformed into symbol strings by means of several discretization methods and a distance based on a kernel between symbols in ordinal scale is used to calculate the similarity between time series. Hence, the idea proposed is the consideration of the simultaneous use of symbolic representation together with a kernel based approach for classification of time series. The methodology has been tested and compared with quantitative learning from a television-viewing shared data set and has yielded a high success identification ratio.Ministerio de Educación y Ciencia TSI2006-13390-C02-02Junta de Andalucía P06-TIC-0214