A framework for exploratory analysis of extreme weather events using geostatistical procedures and 3D self-organizing maps

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FOUR-LAYER SPHERICAL SELF-ORGANIZED MAPS NEURAL NETWORKS TRAINED BY RECIRCULATION TO SIMULATE PERCEPTION AND ABSTRACTION ACTIVITY - APPLICATION TO PATTERNS OF RAINFALL GLOBAL REANALYSIS

This work is intended to organize a big set of time series. To do that a self-organized map is implemented in four spherical layers trained by recirculation. This way tries to simulate aspects of perception and abstraction. The methodology and the fundamentals are described. About the fundamentals, both from the problem point of view and the neural aspects as brain functioning, perception and abstraction concepts, psycho genetics and grouping ideas, and from the architecture of the network, scheme of training, spherical layers of the maps and algorithms involved in the iterative training. Then, it is used to organize a big set of time series of rainfall reanalysis on grid point around the Earth to show how it functions. After removing the average from the series, the annual cycle in shape and amplitude is the main criterion for organization. It is shown how the successive layers contain more general abstractions, their representativeness around the Globe and in regional scale. It is compared with individual series in some points of grid. A possible change of behaviour is found in global scale around 1973 and with a variant in the methodology a possible change in the annual cycle the same year

Exploratory data analysis using self-organising maps defined in up to three dimensions

The SOM is an artificial neural network based on an unsupervised learning process that performs a nonlinear mapping of high dimensional input data onto an ordered and structured array of nodes, designated as the SOM output space. Being simultaneously a quantization algorithm and a projection algorithm, the SOM is able to summarize and map the data, allowing its visualization. Because using the most common visualization methods it is very difficult or even impossible to visualize the SOM defined with more than two dimensions, the SOM output space is generally a regular two dimensional grid of nodes. However, there are no theoretical problems in generating SOMs with higher dimensional output spaces. In this thesis we present evidence that the SOM output space defined in up to three dimensions can be used successfully for the exploratory analysis of spatial data, two-way data and three-way data. Although the differences between the methods that are proposed to visualize each group of data, the approach adopted is commonly based in the projection of colour codes, which are obtained from the output space of 3D SOMs, in some specific bi-dimensional surface, where data can be represented according to its own characteristics. This approach is, in some cases, also complemented with the simultaneous use of SOMs defined in one and two dimensions, so that patterns in data can be properly revealed. The results obtained by using this visualization strategy indicates not only the benefits of using the SOM defined in up to three dimensions but also shows the relevance of the combined and simultaneous use of different models of the SOM in exploratory data analysis

Identificação de Fatores Determinantes

A pirataria marítima é atualmente um fenómeno com forte impacto na atividade económica mundial. Atenta a sua natureza adaptativa e criminosa, tende a evoluir, quer seja no espaço e nas formas de ataque em função das medidas de segurança e proteção que são tomadas por parte dos estados costeiros e das potências marítimas que tomam a iniciativa de prevenir esses mesmos ataques. Regra geral, é possível afirmar que este fenómeno é mais comum em áreas que cruzam as rotas de comércio marítimo e onde se verifica pouco controlo dos estados costeiros. O presente estudo, efetuado com os dados disponibilizados pela InternationalMaritimeOrganization e pelo Centro de Gestão e Análise de Dados Operacionais da Marinha Portuguesa, relativos aos últimos doze anos, tem como objetivo apresentar uma análise exploratória dos dados e verificar se existem padrões nos ataques de pirataria que permitam induzir conhecimento sobre as caraterísticas do fenómeno, na perspectiva espacial e temporal. Para o efeito, foram utilizadas abordagens estatísticas descritivas, recurso a sistemas de informação geográfica e ao uso de Self-OrganizingMaps, definidos com uma, duas e três dimensões no espaço de output com vista à identificação de eventuais padrões existentes nos dados. Da análise efetuada foi possível relacionar os ataques de pirataria entre as áreas afetadas bem como as semelhanças existentes entre eles. Da análise temporal efetuada foi ainda possível analisar a evolução do fenómeno ao longo dos últimos anos.Maritime piracy is currently a phenomenon with a strong impact on global economic activity. Aware of its adaptive and criminal nature, it tends to evolve, whether in space and in the forms of attack depending on the security and protection measures that are taken by coastal states and maritime powers that take the initiative to prevent these same attacks. As a general rule, it can be said that this phenomenon is more common in areas that cross maritime trade routes and where there is little control of coastal states. This study, carried out with the data provided by the InternationalMaritimeOrganization and the Center for Operational Data Management and Analysis of the Portuguese Navy, for the last twelve years, aims to present an exploratory analysis of the data and verify if there are patterns in piracy attacks that allow to induce knowledge about the characteristics of the phenomenon, from a spatial and temporal perspective. For this purpose, were used descriptive statistical approaches, geographic information systems and Self-Organizing Maps, defined with one, two and three dimensions in the output space in order to identify possible patterns in the data. From the analysis performed it was possible to relate the piracy attacks between the affected areas as well as the similarities between them. From the temporal analysis carried out it was also possible to analyze the evolution of the phenomenon over the last few years