142 resultados para Stochastic processes - Computer simulation
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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The minority game (MG) model introduced recently provides promising insights into the understanding of the evolution of prices, indices and rates in the financial markets. In this paper we perform a time series analysis of the model employing tools from statistics, dynamical systems theory and stochastic processes. Using benchmark systems and a financial index for comparison, several conclusions are obtained about the generating mechanism for this kind of evolution. The motion is deterministic, driven by occasional random external perturbation. When the interval between two successive perturbations is sufficiently large, one can find low dimensional chaos in this regime. However, the full motion of the MG model is found to be similar to that of the first differences of the SP500 index: stochastic, nonlinear and (unit root) stationary. (C) 2002 Elsevier B.V. B.V. All rights reserved.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Nos últimos anos houve uma contribuição significativa dos físicos para a construção de um tipo de modelo baseado em agentes que busca reproduzir, em simulação computacional, o comportamento do mercado financeiro. Esse modelo, chamado Jogo da Minoria consiste de um grupo de agentes que vão ao mercado comprar ou vender ativos. Eles tomam decisões com base em estratégias e, por meio delas, os agentes estabelecem um intrincado jogo de competição e coordenação pela distribuição da riqueza. O modelo tem demonstrado resultados bastante ricos e surpreendentes, tanto na dinâmica do sistema como na capacidade de reproduzir características estatísticas e comportamentais do mercado financeiro. Neste artigo, são apresentadas a estrutura e a dinâmica do Jogo da Minoria, bem como as contribuições recentes relacionadas ao Jogo da Minoria denominado de Grande Canônico, que é um modelo mais bem ajustado às características do mercado financeiro e reproduz as regularidades estatísticas do preço dos ativos chamadas fatos estilizados.
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A computer-assisted method for analysing photoacoustic spectra has been developed in the Windows(TM) environment with the use of an easy graphical interface, the computer simulation was carried out with the aim of using the entire expression of the Rosencwaig-Gersho theory, thus permitting multiple applications. The simulation was applied to a system that mimics the electron transfer process in which the concentration of octaethylporphin donor molecules was constant whereas the concentration of duroquinone and 2,3-dichloro-5,6-dicyano-1, l-benzoquinone acceptor molecules varied. The increment of the acceptor concentration influenced the photoacoustic amplitude and phase signals. In the phase signal a significant shift to smaller values was observed, denoting a faster heat generation. The analysis of the photoacoustic signal enabled the determination of the thermal diffusivity, the result obtained through the simulation was about (7 +/- 1) x 10(-7) m(2) s(-1) indicating that changes in the photoacoustic phase signals were due to the electron transfer process rather than changes in the thermal properties of the sample.
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Power-law distributions have been observed in various economical and physical systems. Levy flights have infinite variance which discourage a physical approach. We introduce a class of stochastic processes, the gradually truncated Levy flight in which large steps of a Levy flight are gradually eliminated. It has finite variance and the system can be analyzed in a closed form. We applied the present method to explain the distribution of a particular economical index. The present method can be applied to describe time series in a variety of fields, i.e. turbulent flow, anomalous diffusion, polymers, etc. (C) 1999 Elsevier B.V. B.V. All rights reserved.
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Concept drift is a problem of increasing importance in machine learning and data mining. Data sets under analysis are no longer only static databases, but also data streams in which concepts and data distributions may not be stable over time. However, most learning algorithms produced so far are based on the assumption that data comes from a fixed distribution, so they are not suitable to handle concept drifts. Moreover, some concept drifts applications requires fast response, which means an algorithm must always be (re) trained with the latest available data. But the process of labeling data is usually expensive and/or time consuming when compared to unlabeled data acquisition, thus only a small fraction of the incoming data may be effectively labeled. Semi-supervised learning methods may help in this scenario, as they use both labeled and unlabeled data in the training process. However, most of them are also based on the assumption that the data is static. Therefore, semi-supervised learning with concept drifts is still an open challenge in machine learning. Recently, a particle competition and cooperation approach was used to realize graph-based semi-supervised learning from static data. In this paper, we extend that approach to handle data streams and concept drift. The result is a passive algorithm using a single classifier, which naturally adapts to concept changes, without any explicit drift detection mechanism. Its built-in mechanisms provide a natural way of learning from new data, gradually forgetting older knowledge as older labeled data items became less influent on the classification of newer data items. Some computer simulation are presented, showing the effectiveness of the proposed method.
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Teaching a course of special electric loads in a continuing education program to power engineers is a difficult task because they are not familiarized with switching topology circuits. Normally, in a typical program, many hours are dedicated to explain the thyristors switching sequence and to draw the converter currents and terminal voltages waveforms for different operative conditions. This work presents teaching support software in order to optimize the time spent in this task and, mainly to benefit the assimilation of the proposed subjects, studying the static converter under different non-ideal operative conditions.
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An experimental model and a mathematical model with the introduction of a ramp in the channel of Obenaus model are presented. The aim is to present a better reproduction of the real layer pollution deposited on the HV insulators. This better reproduction is obtained from two types of thickness variation: the introduction of a ramp (soft variation) and the introduction of a step (sudden variation). The computational simulations and the experimental data suggest that the introduction of the ramp is the better reproduction of the layer pollution. The ramp approximates to the real layer pollution more than the step.
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The Backpropagation Algorithm (BA) is the standard method for training multilayer Artificial Neural Networks (ANN), although it converges very slowly and can stop in a local minimum. We present a new method for neural network training using the BA inspired on constructivism, an alphabetization method proposed by Emilia Ferreiro based on Piaget philosophy. Simulation results show that the proposed configuration usually obtains a lower final mean square error, when compared with the standard BA and with the BA with momentum factor.
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An algorithm for adaptive IIR filtering that uses prefiltering structure in direct form is presented. This structure has an estimation error that is a linear function of the coefficients. This property greatly simplifies the derivation of gradient-based algorithms. Computer simulations show that the proposed structure improves convergence speed.
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The performance of the three-phase core type transformers, under AC/DC double excitation is discussed in this work. It is presented a mathematical model that considers the mutual coupling between phases and the magnetic nonlinearity. The validity of the proposed model is verified by means of the experimental and simulated results.
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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This work presents a numerical model to simulate refrigerant flow through capillary tubes, commonly used as expansion devices in refrigeration systems. The capillary tube is considered straight and horizontal. The flow is taken as one-dimensional and adiabatic. Steady state and thermodynamic equilibrium conditions are assumed. The two-fluid model, involving four conservation equations and considering the hidrodynamic nonequilibrium between the liquid and vapor phases is applied to the flow region. The pressure profiles and the mass flow rates given by the model are compared with experimental data.