12 resultados para Ceará State


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Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para a obtenção do Grau de Mestre em Engenharia Informática

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Journal of Cleaner Production, nº 17, p. 36-52

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African Studies Review, Volume 52, Number 2, pp. 35–

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Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores Mestrado Integrado em Engenharia Electrotécnica e de Computadores

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Dissertação para obtenção do Grau de Mestre em Engenharia Mecânica

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Tese apresentada para cumprimento dos requisitos necessários à obtenção do grau de Doutor em Ciência Política, especialidade de Teoria e Análise Política.

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Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics

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Dissertação para obtenção do Grau de Mestre em Bioquímica Estrutural e Funcional

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Dissertação para obtenção do Grau de Mestre em Energia e Bioenergia

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International Conference on Vernacular Heritage, Sustainability and Earthen Architecture, VerSus 2014, 2nd MEDITERRA, 2nd ResTAPIA, 11-13 September, Valencia, Spain

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This study analyses financial data using the result characterization of a self-organized neural network model. The goal was prototyping a tool that may help an economist or a market analyst to analyse stock market series. To reach this goal, the tool shows economic dependencies and statistics measures over stock market series. The neural network SOM (self-organizing maps) model was used to ex-tract behavioural patterns of the data analysed. Based on this model, it was de-veloped an application to analyse financial data. This application uses a portfo-lio of correlated markets or inverse-correlated markets as input. After the anal-ysis with SOM, the result is represented by micro clusters that are organized by its behaviour tendency. During the study appeared the need of a better analysis for SOM algo-rithm results. This problem was solved with a cluster solution technique, which groups the micro clusters from SOM U-Matrix analyses. The study showed that the correlation and inverse-correlation markets projects multiple clusters of data. These clusters represent multiple trend states that may be useful for technical professionals.