994 resultados para Iberian bronzes
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P and S receiver functions (PRF and SRF) from 19 seismograph stations in the Gibraltar Arc and the Iberian Massif reveal new details of the regional deep structure. Within the high-velocity mantle body below southern Spain the 660-km discontinuity is depressed by at least 20 km. The Ps phase from the 410-km discontinuity is missing at most stations in the Gibraltar Arc. A thin (similar to 50 km) low-S-velocity layer atop the 410-km discontinuity is found under the Atlantic margin. At most stations the S410p phase in the SRFs arrives 1.0-2.5 s earlier than predicted by IASP91 model, but, for the propagation paths through the upper mantle below southern Spain, the arrivals of S410p are delayed by up to +1.5 s. The early arrivals can be explained by elevated Vp/Vs ratio in the upper mantle or by a depressed 410-km discontinuity. The positive residuals are indicative of a low (similar to 1.7 versus similar to 1.8 in IASP91) Vp/Vs ratio. Previously, the low ratio was found in depleted lithosphere of Precambrian cratons. From simultaneous inversion of the PRFs and SRFs we recognize two types of the mantle: 'continental' and 'oceanic'. In the 'continental' upper mantle the S-wave velocity in the high-velocity lid is 4.4-4.5 km s(-1), the S-velocity contrast between the lid and the underlying mantle is often near the limit of resolution (0.1 km s(-1)), and the bottom of the lid is at a depth reaching 90 100 km. In the 'oceanic' domain, the S-wave velocities in the lid and the underlying mantle are typically 4.2-4.3 and similar to 4.0 km s(-1), respectively. The bottom of the lid is at a shallow depth (around 50 km), and at some locations the lid is replaced by a low S-wave velocity layer. The narrow S-N-oriented band of earthquakes at depths from 70 to 120 km in the Alboran Sea is in the 'continental' domain, near the boundary between the 'continental' and 'oceanic' domains, and the intermediate seismicity may be an effect of ongoing destruction of the continental lithosphere.
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In this paper, we present a deterministic approach to tsunami hazard assessment for the city and harbour of Sines, Portugal, one of the test sites of project ASTARTE (Assessment, STrategy And Risk Reduction for Tsunamis in Europe). Sines has one of the most important deep-water ports, which has oil-bearing, petrochemical, liquid-bulk, coal, and container terminals. The port and its industrial infrastructures face the ocean southwest towards the main seismogenic sources. This work considers two different seismic zones: the Southwest Iberian Margin and the Gloria Fault. Within these two regions, we selected a total of six scenarios to assess the tsunami impact at the test site. The tsunami simulations are computed using NSWING, a Non-linear Shallow Water model wIth Nested Grids. In this study, the static effect of tides is analysed for three different tidal stages: MLLW (mean lower low water), MSL (mean sea level), and MHHW (mean higher high water). For each scenario, the tsunami hazard is described by maximum values of wave height, flow depth, drawback, maximum inundation area and run-up. Synthetic waveforms are computed at virtual tide gauges at specific locations outside and inside the harbour. The final results describe the impact at the Sines test site considering the single scenarios at mean sea level, the aggregate scenario, and the influence of the tide on the aggregate scenario. The results confirm the composite source of Horseshoe and Marques de Pombal faults as the worst-case scenario, with wave heights of over 10 m, which reach the coast approximately 22 min after the rupture. It dominates the aggregate scenario by about 60 % of the impact area at the test site, considering maximum wave height and maximum flow depth. The HSMPF scenario inundates a total area of 3.5 km2. © Author(s) 2015.
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In machine learning and pattern recognition tasks, the use of feature discretization techniques may have several advantages. The discretized features may hold enough information for the learning task at hand, while ignoring minor fluctuations that are irrelevant or harmful for that task. The discretized features have more compact representations that may yield both better accuracy and lower training time, as compared to the use of the original features. However, in many cases, mainly with medium and high-dimensional data, the large number of features usually implies that there is some redundancy among them. Thus, we may further apply feature selection (FS) techniques on the discrete data, keeping the most relevant features, while discarding the irrelevant and redundant ones. In this paper, we propose relevance and redundancy criteria for supervised feature selection techniques on discrete data. These criteria are applied to the bin-class histograms of the discrete features. The experimental results, on public benchmark data, show that the proposed criteria can achieve better accuracy than widely used relevance and redundancy criteria, such as mutual information and the Fisher ratio.
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Dissertação de Mestrado apresentada ao Instituto de Contabilidade e Administração do Porto para a obtenção do grau de Mestre em Contabilidade e Finanças, sob orientação do Dr. Luís Pereira Gomes
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Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Civil
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Com este trabalho pretende-se efetuar o levantamento e análise dos fatores que estão na base da volatilidade do preço da energia elétrica no mercado ibérico de energia. Posteriormente à definição dos potenciais métodos utilizados na previsão do preço da energia elétrica, é desenvolvido um modelo capaz de prever os preços do mercado de energia para um horizonte de vários períodos temporais (trimestral, mensal, semanal e diário). Por fim são comparados os resultados dos modelos aplicados, tendo como base a análise qualitativa e quantitativa da evolução das respetivas previsões, bem como a análise estatística obtida em cada um deles.
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A evolução dos transportes de mercadorias, em Portugal e na União Europeia, assume uma enorme repercussão na economia global, de modo que a combinação dos vários modos de transporte, com vista à obtenção de ganhos ao nível da eficiência, adquire extrema importância. Os programas europeus de apoio aos transportes, enquadrados na rede transeuropeia de transportes e plataformas logísticas, também contribuem para a otimização do transporte de mercadorias. A importância do transporte ferroviário de mercadorias no eixo Leixões- Salamanca, nomeadamente para as empresas exportadoras e importadoras da região norte e centro, que utilizam meios alternativos ao ferroviário, constitui o principal objetivo desta dissertação. A revisão bibliográfica inclui uma abordagem aos transportes de mercadorias em geral e de forma mais aprofundada aos modos ferroviário e rodoviário na península ibérica, passando pela logística, bem como pela integração de modos: intermodalidade e multimodalidade na rede europeia de transportes e ainda a referência aos portos secos e às plataformas logísticas. Isto permite caraterizar as diferentes empresas operadoras do setor dos transportes de mercadorias e os produtos transacionados, assim como enumerar vantagens e/ou desvantagens do meio de transporte ferroviário face a outros meios, mais concretamente no eixo alvo deste estudo. A metodologia utilizada consiste na análise de informação proveniente de fontes secundárias havendo lugar a uma referência mais detalhada sobre as plataformas logísticas de Leixões e Salamanca, o eixo E-80, o corredor ferroviário nº4 e os programas europeus promotores da eficiência no transporte ferroviário de mercadorias: Marathon, Ferremed e Marco Polo. Para a recolha de informação primária o instrumento adotado foi a entrevista semiestruturada, efetuada a dois representantes da empresa CP-Carga e a um representante da empresa KLog, ambas as empresas ligadas ao setor dos transportes e logística. A análise e tratamento de toda a informação recolhida possibilitam, desde logo, evidenciar as potencialidades do eixo Leixões-Salamanca no que se refere ao transporte ferroviário de mercadorias, delinear recomendações para a sua otimização, bem como efetuar uma análise SWOT. As considerações finais revelam que é imperativo adotar medidas, de forma integrada, para que o seu efeito na potenciação do transporte ferroviário de mercadorias, não só no eixo Leixões-Salamanca, mas também a nível europeu, se afirme como uma verdadeira alternativa a outros modos, particularmente ao domínio rodoviário.
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The existence of satellite images ofthe West Iberian Margin allowed comparative study of images as a tool applied to structural geology. Interpretation of LANDSAT images of the Lusitanian Basin domain showed the existence of a not previously described WNW-ESE trending set oflineaments. These lineaments are persistent and only observable on small scale images (e.g. approx. 11200000 and 11500 000) with various radiometric characteristics. They are approximately 20 km long, trend l200±15° and cross cut any other families oflineaments. The fact that these lineaments are perpendicular to the Quaternary thrusts of the Lower Tagus Valley and also because they show no off-set across them, suggests that they resulted from intersection oflarge tensile fractures on the earth's surface. It is proposed in this work that these lineaments formed on a crustal flexure of tens ofkm long, associated with the Quaternary WNW-ESE oriented maximum compressive stress on the West Iberian Margin. The maximum compressive stress rotated anticlockwise from a NW -SE orientation to approximately WNW-ESE, from Late Miocene to Quaternary times (RIBEIRO et aI., 1996). Field inspection of the lineaments revealed zones of norm~1.J. faulting and cataclasis, which are coincident with the lineaments and affect sediments of upper Miocene up to Quaternary age. These deformation structures show localized extension perpendicular to the lineaments, i.e. perpendicular to the maximum compressive direction, after recent stress data along the West Portuguese Margin (CABRAL & RIBEIRO, 1989; RIBEIRO et at., 1996). Also, on a first approach, the geographical distribution of these lineaments correlates well with earthquake epicenters and areas of largest Quaternary Vertical Movements within the inverted Lusitanian Basin (CABRAL, 1995).
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Electricity Markets are not only a new reality but an evolving one as the involved players and rules change at a relatively high rate. Multi-agent simulation combined with Artificial Intelligence techniques may result in very helpful sophisticated tools. This paper presents a new methodology for the management of coalitions in electricity markets. This approach is tested using the multi-agent market simulator MASCEM (Multi-Agent Simulator of Competitive Electricity Markets), taking advantage of its ability to provide the means to model and simulate Virtual Power Players (VPP). VPPs are represented as coalitions of agents, with the capability of negotiating both in the market and internally, with their members in order to combine and manage their individual specific characteristics and goals, with the strategy and objectives of the VPP itself. A case study using real data from the Iberian Electricity Market is performed to validate and illustrate the proposed approach.
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Energy systems worldwide are complex and challenging environments. Multi-agent based simulation platforms are increasing at a high rate, as they show to be a good option to study many issues related to these systems, as well as the involved players at act in this domain. In this scope the authors’ research group has developed a multi-agent system: MASCEM (Multi- Agent System for Competitive Electricity Markets), which simulates the electricity markets environment. MASCEM is integrated with ALBidS (Adaptive Learning Strategic Bidding System) that works as a decision support system for market players. The ALBidS system allows MASCEM market negotiating players to take the best possible advantages from the market context. This paper presents the application of a Support Vector Machines (SVM) based approach to provide decision support to electricity market players. This strategy is tested and validated by being included in ALBidS and then compared with the application of an Artificial Neural Network, originating promising results. The proposed approach is tested and validated using real electricity markets data from MIBEL - Iberian market operator.
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Energy systems worldwide are complex and challenging environments. Multi-agent based simulation platforms are increasing at a high rate, as they show to be a good option to study many issues related to these systems, as well as the involved players at act in this domain. In this scope the authors’ research group has developed a multi-agent system: MASCEM (Multi- Agent System for Competitive Electricity Markets), which performs realistic simulations of the electricity markets. MASCEM is integrated with ALBidS (Adaptive Learning Strategic Bidding System) that works as a decision support system for market players. The ALBidS system allows MASCEM market negotiating players to take the best possible advantages from each market context. However, it is still necessary to adequately optimize the players’ portfolio investment. For this purpose, this paper proposes a market portfolio optimization method, based on particle swarm optimization, which provides the best investment profile for a market player, considering different market opportunities (bilateral negotiation, market sessions, and operation in different markets) and the negotiation context such as the peak and off-peak periods of the day, the type of day (business day, weekend, holiday, etc.) and most important, the renewable based distributed generation forecast. The proposed approach is tested and validated using real electricity markets data from the Iberian operator – MIBEL.
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Electricity markets are complex environments, involving a large number of different entities, with specific characteristics and objectives, making their decisions and interacting in a dynamic scene. Game-theory has been widely used to support decisions in competitive environments; therefore its application in electricity markets can prove to be a high potential tool. This paper proposes a new scenario analysis algorithm, which includes the application of game-theory, to evaluate and preview different scenarios and provide players with the ability to strategically react in order to exhibit the behavior that better fits their objectives. This model includes forecasts of competitor players’ actions, to build models of their behavior, in order to define the most probable expected scenarios. Once the scenarios are defined, game theory is applied to support the choice of the action to be performed. Our use of game theory is intended for supporting one specific agent and not for achieving the equilibrium in the market. MASCEM (Multi-Agent System for Competitive Electricity Markets) is a multi-agent electricity market simulator that models market players and simulates their operation in the market. The scenario analysis algorithm has been tested within MASCEM and our experimental findings with a case study based on real data from the Iberian Electricity Market are presented and discussed.
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Energy systems worldwide are complex and challenging environments. Multi-agent based simulation platforms are increasing at a high rate, as they show to be a good option to study many issues related to these systems, as well as the involved players at act in this domain. In this scope the authors’ research group has developed a multi-agent system: MASCEM (Multi-Agent System for Competitive Electricity Markets), which simulates the electricity markets. MASCEM is integrated with ALBidS (Adaptive Learning Strategic Bidding System) that works as a decision support system for market players. The ALBidS system allows MASCEM market negotiating players to take the best possible advantages from the market context. However, it is still necessary to adequately optimize the player’s portfolio investment. For this purpose, this paper proposes a market portfolio optimization method, based on particle swarm optimization, which provides the best investment profile for a market player, considering the different markets the player is acting on in each moment, and depending on different contexts of negotiation, such as the peak and offpeak periods of the day, and the type of day (business day, weekend, holiday, etc.). The proposed approach is tested and validated using real electricity markets data from the Iberian operator – OMIE.
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This paper presents a decision support methodology for electricity market players’ bilateral contract negotiations. The proposed model is based on the application of game theory, using artificial intelligence to enhance decision support method’s adaptive features. This model is integrated in AiD-EM (Adaptive Decision Support for Electricity Markets Negotiations), a multi-agent system that provides electricity market players with strategic behavior capabilities to improve their outcomes from energy contracts’ negotiations. Although a diversity of tools that enable the study and simulation of electricity markets has emerged during the past few years, these are mostly directed to the analysis of market models and power systems’ technical constraints, making them suitable tools to support decisions of market operators and regulators. However, the equally important support of market negotiating players’ decisions is being highly neglected. The proposed model contributes to overcome the existing gap concerning effective and realistic decision support for electricity market negotiating entities. The proposed method is validated by realistic electricity market simulations using real data from the Iberian market operator—MIBEL. Results show that the proposed adaptive decision support features enable electricity market players to improve their outcomes from bilateral contracts’ negotiations.
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Dissertação para obtenção do Grau de Doutor em Conservação e Restauro, especialidade Ciências da Conservação