Computational Intelligence Techniques for Predicting Earthquakes

Nowadays, much effort is being devoted to develop techniques that forecast natural disasters in order to take precautionary measures. In this paper, the extraction of quantitative association rules and regression techniques are used to discover patterns which model the behavior of seismic temporal data to help in earthquakes prediction. Thus, a simple method based on the k–smallest and k–greatest values is introduced for mining rules that attempt at explaining the conditions under which an earthquake may happen. On the other hand patterns are discovered by using a tree-based piecewise linear model. Results from seismic temporal data provided by the Spanish’s Geographical Institute are presented and discussed, showing a remarkable performance and the significance of the obtained results.Ministerio de Ciencia y tecnología TIN2007-68084-C-02Junta de Andalucía P07-TIC-0261

A novel tree-based algorithm to discover seismic patterns in earthquake catalogs

A novel methodology is introduced in this research study to detect seismic precursors. Based on an existing approach, the new methodology searches for patterns in the historical data. Such patterns may contain statistical or soil dynamics information. It improves the original version in several aspects. First, new seismicity indicators have been used to characterize earthquakes. Second, a machine learning clustering algorithm has been applied in a very flexible way, thus allowing the discovery of new data groupings. Third, a novel search strategy is proposed in order to obtain non-overlapped patterns. And, fourth, arbitrary lengths of patterns are searched for, thus discovering long and short-term behaviors that may influence in the occurrence of medium-large earthquakes. The methodology has been applied to seven different datasets, from three different regions, namely the Iberian Peninsula, Chile and Japan. Reported results show a remarkable improvement with respect to the former version, in terms of all evaluated quality measures. In particular, the number of false positives has decreased and the positive predictive values increased, both of them in a very remarkable manner.Ministerio de Ciencia y Tecnología TIN2011-28956-C00Junta de Andalucía P12-TIC-1728Instituto Ramón y Cajal (RYC) RYC-2012-1198

Selecting the best measures to discover quantitative association rules

The majority of the existing techniques to mine association rules typically use the support and the confidence to evaluate the quality of the rules obtained. However, these two measures may not be sufficient to properly assess their quality due to some inherent drawbacks they present. A review of the literature reveals that there exist many measures to evaluate the quality of the rules, but that the simultaneous optimization of all measures is complex and might lead to poor results. In this work, a principal components analysis is applied to a set of measures that evaluate quantitative association rules' quality. From this analysis, a reduced subset of measures has been selected to be included in the fitness function in order to obtain better values for the whole set of quality measures, and not only for those included in the fitness function. This is a general-purpose methodology and can, therefore, be applied to the fitness function of any algorithm. To validate if better results are obtained when using the function fitness composed of the subset of measures proposed here, the existing QARGA algorithm has been applied to a wide variety of datasets. Finally, a comparative analysis of the results obtained by means of the application of QARGA with the original fitness function is provided, showing a remarkable improvement when the new one is used.Ministerio de Ciencia y Tecnología TIN2011-28956-C0

Técnicas de IA para el estudio de datos geomagnéticos y su implementación como precursores sísmicos: estado del arte

This work presents the results of the development of a state of the art with topics related to the analysis of intelligent systems using geomagnetic data, present in the ionosphere, implementing AI (Artificial Intelligence) techniques for the development of possible seismic precursors; the mentioned work has as objective the revision of AI techniques and/or algorithms, programming languages, parameters of interest and databases. As a result of the research, 106 documents were obtained, consisting of theses, journal articles, and exhibitions in congresses by means of posters, of national and international character; it was concluded that within the techniques and/or algorithms investigated, the Convolutional Neural Networks (ANN), Support Vector Machines (SVM), Decision Trees and K-MEANS stand out; these techniques are useful to observe the behavior of the data and to find patterns in the information.  Este trabajo presenta los resultados del desarrollo de un estado del arte con temas relacionados con el análisis de sistemas inteligentes utilizando datos geomagnéticos, presentes en la ionosfera, implementando técnicas de IA (Inteligencia Artificial) para el desarrollo de posibles precursores sísmicos; el trabajo mencionado tiene como objetivo la revisión de técnicas y/o algoritmos de IA, lenguajes de programación, parámetros de interés y bases de datos. Como resultado de la investigación, se obtuvieron 106 documentos conformados por tesis, artículos de revistas, y exposiciones en congresos por medio de carteles, de carácter nacional e internacional; se concluyó que dentro de las técnicas y/o algoritmos investigados destacan las Redes Neuronales Convolucionales (ANN), Máquina Vectores de Soporte (SVM), Árboles de decisión y K-MEANS, estas técnicas son de utilidad para observar el comportamiento de los datos y encontrar patrones en la información

Determining the best set of seismicity indicators to predict earthquakes. Two case studies: Chile and the Iberian Peninsula

This work explores the use of different seismicity indicators as inputs for artificial neural networks. The combination of multiple indicators that have already been successfully used in different seismic zones by the application of feature selection techniques is proposed. These techniques evaluate every input and propose the best combination of them in terms of information gain. Once these sets have been obtained, artificial neural networks are applied to four Chilean zones (the most seismic country in the world) and to two zones of the Iberian Peninsula (a moderate seismicity area). To make the comparison to other models possible, the prediction problem has been turned into one of classification, thus allowing the application of other machine learning classifiers. Comparisons with original sets of inputs and different classifiers are reported to support the degree of success achieved. Statistical tests have also been applied to confirm that the results are significantly different than those of other classifiers. The main novelty of this work stems from the use of feature selection techniques for improving earthquake prediction methods. So, the infor-mation gain of different seismic indicators has been determined. Low ranked or null contribution seismic indicators have been removed, optimizing the method. The optimized prediction method proposed has a high performance. Finally, four Chilean zones and two zones of the Iberian Peninsula have been charac-terized by means of an information gain analysis obtained from different seismic indicators. The results confirm the methodology proposed as the best features in terms of information gain are the same for both regions.Ministerio de Ciencia y Tecnología BIA2004-01302Ministerio de Ciencia y Tecnología TIN2011-28956-C02-01Junta de Andalucía P11-TIC-752

The protection of privacy in the technological age: towards a reconceptualización

URL del artículo en la web de la Revista: https://www.upo.es/revistas/index.php/ripp/article/view/3683El objetivo de este trabajo es aportar un poco de claridad a la actual confusión en torno al concepto de intimidad en el nuevo contexto tecnológico. Para ello, tenemos en cuenta la amplitud y la complejidad del término sin pretender disipar plenamente la ambigüedad que acompaña a esta noción. Por otro lado, cuestionamos la difícil defensa de los límites herméticos que custodiaban lo íntimo/privado de lo público, superados hoy en día por un ágora virtual desespaciada que permite el tránsito y acumulación ilimitada de información y datospersonales de toda índole. Exponemos brevemente algunos de los dispositivos tecnológicos de seguimiento y vigilancia, almacenamiento y tratamiento de datos y los potentes sistemas de difusión de la información como Internet. Las nuevas amenazas que atentan contra la intimidad nos llevan a examinar las tesis de algunos autores con el fi n de aportar nuevos horizontes de análisis y re flexión sobre una construcción jurídica moderna que ha de evolucionar y de finirse para responder ante esos nuevos desafíos.The objective of this paper is to bring some clarity to the current confusion surrounding the concept of privacy in the new technological context. To do it, we explain the breadth and complexity of the term without attempting fully dispel the ambiguity that accompanies this no- tion. On the other hand, we analyze the dif fi cult question of the limits between privacy and public space, now superseded by a virtual agora where unlimited accumulation of information and personal data of all kinds is a reality. To understand this, we describe brie fl y some of the new technological devices surveillance, storage and processing of data and powerful systems of information dissemination as the Internet. The new threats that jeopardize the privacy lead us to examine the arguments of some authors to provide new horizons for analysis and re fl ection on a modern legal construct that has to evolve and be de fi ned to respond to these new challenges.Universidad Pablo de Olavid

LA PROTECCIÓN DE LA INTIMIDAD EN LA ERA TECNOLÓGICA: HACIA UNA RECONCEPTUALIZACIÓN

El objetivo de este trabajo es aportar un poco de claridad a la actual confusión en torno al concepto de intimidad en el nuevo contexto tecnológico. Para ello, tenemos en cuenta la amplitud y la complejidad del término sin pretender disipar plenamente la ambigüedad que acompaña a esta noción. Por otro lado, cuestionamos la difícil defensa de los límites herméticos que custodiaban lo íntimo/privado de lo público, superados hoy en día por un ágora virtual desespaciada que permite el tránsito y acumulación ilimitada de información y datos personales de toda índole. Exponemos brevemente algunos de los dispositivos tecnológicos de seguimiento y vigilancia, almacenamiento y tratamiento de datos y los potentes sistemas de difusión de la información como Internet. Las nuevas amenazas que atentan contra la intimidad nos llevan a examinar las tesis de algunos autores con el fi n de aportar nuevos horizontes de análisis y refl exión sobre una construcción jurídica moderna que ha de evolucionar y defi nirse para responder ante esos nuevos desafíos