6 resultados para randomness

em Instituto Politécnico do Porto, Portugal


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A new general fitting method based on the Self-Similar (SS) organization of random sequences is presented. The proposed analytical function helps to fit the response of many complex systems when their recorded data form a self-similar curve. The verified SS principle opens new possibilities for the fitting of economical, meteorological and other complex data when the mathematical model is absent but the reduced description in terms of some universal set of the fitting parameters is necessary. This fitting function is verified on economical (price of a commodity versus time) and weather (the Earth’s mean temperature surface data versus time) and for these nontrivial cases it becomes possible to receive a very good fit of initial data set. The general conditions of application of this fitting method describing the response of many complex systems and the forecast possibilities are discussed.

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This paper proposes a new methodology to reduce the probability of occurring states that cause load curtailment, while minimizing the involved costs to achieve that reduction. The methodology is supported by a hybrid method based on Fuzzy Set and Monte Carlo Simulation to catch both randomness and fuzziness of component outage parameters of transmission power system. The novelty of this research work consists in proposing two fundamentals approaches: 1) a global steady approach which deals with building the model of a faulted transmission power system aiming at minimizing the unavailability corresponding to each faulted component in transmission power system. This, results in the minimal global cost investment for the faulted components in a system states sample of the transmission network; 2) a dynamic iterative approach that checks individually the investment’s effect on the transmission network. A case study using the Reliability Test System (RTS) 1996 IEEE 24 Buses is presented to illustrate in detail the application of the proposed methodology.

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This paper presents a methodology which is based on statistical failure and repair data of the transmission power system components and uses fuzzyprobabilistic modeling for system component outage parameters. Using statistical records allows developing the fuzzy membership functions of system component outage parameters. The proposed hybrid method of fuzzy set and Monte Carlo simulation based on the fuzzy-probabilistic models allows catching both randomness and fuzziness of component outage parameters. A network contingency analysis to identify any overloading or voltage violation in the network is performed once obtained the system states by Monte Carlo simulation. This is followed by a remedial action algorithm, based on optimal power flow, to reschedule generations and alleviate constraint violations and, at the same time, to avoid any load curtailment, if possible, or, otherwise, to minimize the total load curtailment, for the states identified by the contingency analysis. In order to illustrate the application of the proposed methodology to a practical case, the paper will include a case study for the Reliability Test System (RTS) 1996 IEEE 24 BUS.

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This paper present a methodology to choose the distribution networks reconfiguration that presents the lower power losses. The proposed methodology is based on statistical failure and repair data of the distribution power system components and uses fuzzy-probabilistic modeling for system component outage parameters. The proposed hybrid method using fuzzy sets and Monte Carlo simulation based on the fuzzyprobabilistic models allows catching both randomness and fuzziness of component outage parameters. A logic programming algorithm is applied, once obtained the system states by Monte Carlo Simulation, to get all possible reconfigurations for each system state. To evaluate the line flows and bus voltages and to identify if there is any overloading, and/or voltage violation an AC load flow has been applied to select the feasible reconfiguration with lower power losses. To illustrate the application of the proposed methodology, the paper includes a case study that considers a 115 buses distribution network.

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It has been shown that in reality at least two general scenarios of data structuring are possible: (a) a self-similar (SS) scenario when the measured data form an SS structure and (b) a quasi-periodic (QP) scenario when the repeated (strongly correlated) data form random sequences that are almost periodic with respect to each other. In the second case it becomes possible to describe their behavior and express a part of their randomness quantitatively in terms of the deterministic amplitude–frequency response belonging to the generalized Prony spectrum. This possibility allows us to re-examine the conventional concept of measurements and opens a new way for the description of a wide set of different data. In particular, it concerns different complex systems when the ‘best-fit’ model pretending to be the description of the data measured is absent but the barest necessity of description of these data in terms of the reduced number of quantitative parameters exists. The possibilities of the proposed approach and detection algorithm of the QP processes were demonstrated on actual data: spectroscopic data recorded for pure water and acoustic data for a test hole. The suggested methodology allows revising the accepted classification of different incommensurable and self-affine spatial structures and finding accurate interpretation of the generalized Prony spectroscopy that includes the Fourier spectroscopy as a partial case.

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O intenso intercâmbio entre os países, resultante do processo de globalização, veio acrescer importância ao mercado de capitais. Os países em desenvolvimento procuram abrir as suas economias para receber investimentos externos. Quanto maior for o grau de desenvolvimento de uma economia mais ativo será o seu mercado de capitais. No entanto, tem-se verificado uma tendência de substituição de enfoque económico, que antes era mais dirigido ao planeamento empresarial para metas mais ligadas ao meio ambiente. O mercado de capitais é um sistema de distribuição de valores mobiliários cujo objectivo é proporcionar liquidez a títulos emitidos pelas empresas, com a finalidade de viabilizar o processo de capitalização desses papéis. O mercado de capitais é composto pelas bolsas de valores, sociedades corretoras e outras instituições financeiras que têm autorização da Comissão de Valores dos Mercados Mobiliários (CMVM). O mercado bolsista insere-se no mercado de capitais. Nesses mercados, é importante conseguir conjuntamente a maximização dos recursos (retornos) e minimização dos custos (riscos). O principal objectivo das bolsas de valores é promover um ambiente de negociação dos títulos e dos valores mobiliários das empresas. Muitos investidores têm a sua própria maneira de investir, consoante o perfil que cada um tem. Além do perfil dos investidores, é também pertinente analisar a questão do risco. Vaughan (1997) observa que, nos dias atuais, a questão da administração do risco está presente na vida de todos. Este trabalho tem o propósito de demonstrar a necessidade da utilização de ferramentas para a seleção de ativos e para a mensuração do risco e do retorno de aplicações de recursos financeiros nesses activos de mercados de capitais, por qualquer tipo de investidor, mais especificamente na compra de ações e montagem de uma carteira de investimento. Para isso usou-se o método de Elton e Gruber, analisou-se as rentabilidades, os riscos e os índices de desempenho de Treynor e Sharpe. Testes estatísticos para os retornos das ações foram executados visando analisar a aleatoriedade dos dados. Este trabalho conclui que pode haver vantagens na utilização do método de Elton e Gruber para os investidores propensos a utilzar ações de empresas socialmente responsáveis.