8 resultados para Price forecast
em Repositório Institucional UNESP - Universidade Estadual Paulista "Julio de Mesquita Filho"
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This paper describes a branch-and-price algorithm for the p-median location problem. The objective is to locate p facilities (medians) such as the sum of the distances from each demand point to its nearest facility is minimized. The traditional column generation process is compared with a stabilized approach that combines the column generation and Lagrangean/surrogate relaxation. The Lagrangean/surrogate multiplier modifies; the reduced cost criterion, providing the selection of new productive columns at the search tree. Computational experiments are conducted considering especially difficult instances to the traditional column generation and also with some large-scale instances. (C) 2004 Elsevier Ltd. All rights reserved.
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Relata-se a ocorrência de Learedius learedi Price 1934 (Digenea, Spirorchiidae) em Chelonia mydas Linnaeus 1758 (Testudines, Chelonidae) no Brasil. Onze animais foram examinados e destes, 54,6% estavam parasitados. Duzentos e cinqüenta e cinco exemplares de L. learedi foram recuperados de órgãos (coração, fígado, baço, pulmões, rins, mesentério) e do lavado corporal dos animais. Os resultados contribuem para o conhecimento da helmintofauna de quelônios marinhos e sua distribuição geográfica. Este é o primeiro registro da ocorrência de L. learedi na região do Atlântico Sul Ocidental.
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We investigate the Heston model with stochastic volatility and exponential tails as a model for the typical price fluctuations of the Brazilian São Paulo Stock Exchange Index (IBOVESPA). Raw prices are first corrected for inflation and a period spanning 15 years characterized by memoryless returns is chosen for the analysis. Model parameters are estimated by observing volatility scaling and correlation properties. We show that the Heston model with at least two time scales for the volatility mean reverting dynamics satisfactorily describes price fluctuations ranging from time scales larger than 20min to 160 days. At time scales shorter than 20 min we observe autocorrelated returns and power law tails incompatible with the Heston model. Despite major regulatory changes, hyperinflation and currency crises experienced by the Brazilian market in the period studied, the general success of the description provided may be regarded as an evidence for a general underlying dynamics of price fluctuations at intermediate mesoeconomic time scales well approximated by the Heston model. We also notice that the connection between the Heston model and Ehrenfest urn models could be exploited for bringing new insights into the microeconomic market mechanics. (c) 2005 Elsevier B.V. All rights reserved.
Resumo:
Managing the great complexity of enterprise system, due to entities numbers, decision and process varieties involved to be controlled results in a very hard task because deals with the integration of its operations and its information systems. Moreover, the enterprises find themselves in a constant changing process, reacting in a dynamic and competitive environment where their business processes are constantly altered. The transformation of business processes into models allows to analyze and redefine them. Through computing tools usage it is possible to minimize the cost and risks of an enterprise integration design. This article claims for the necessity of modeling the processes in order to define more precisely the enterprise business requirements and the adequate usage of the modeling methodologies. Following these patterns, the paper concerns the process modeling relative to the domain of demand forecasting as a practical example. The domain of demand forecasting was built based on a theoretical review. The resulting models considered as reference model are transformed into information systems and have the aim to introduce a generic solution and be start point of better practical forecasting. The proposal is to promote the adequacy of the information system to the real needs of an enterprise in order to enable it to obtain and accompany better results, minimizing design errors, time, money and effort. The enterprise processes modeling are obtained with the usage of CIMOSA language and to the support information system it was used the UML language.
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Automotive parts manufacture by machining process using silicon nitride-based ceramic tool development in Brazil already is a reality. Si 3N4-based ceramic cutting tools offer a high productivity due to their excellent hot hardness, which allows high cutting speeds. Under such conditions the cutting tool must be resistant to a combination of mechanical, thermal and chemical attacks. Silicon nitride based ceramic materials constitute a mature technology with a very broad base of current and potential applications. The best opportunities for Si3N 4-based ceramics include ballistic armor, composite automotive brakes, diesel particulate filters, joint replacement products and others. The goal of this work was to show latter advance in silicon nitride manufacture and its recent evolution on machining process of gray cast iron, compacted graphite iron and Ti-6Al-4V. Materials characterization and machining tests were analyzed by X-Ray Diffraction, Scanning Electron Microscopy, Vickers hardness and toughness fracture and technical norm. In recent works the authors has been proved to advance in microstructural, mechanical and physic properties control. These facts prove that silicon nitride-based ceramic has enough resistance to withstand the impacts inherent to the machining of gray cast iron (CI), compacted graphite iron (CGI) and Ti-6Al-4V (6-4). Copyright © 2008 SAE International.
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Considering the importance of spatial issues in transport planning, the main objective of this study was to analyze the results obtained from different approaches of spatial regression models. In the case of spatial autocorrelation, spatial dependence patterns should be incorporated in the models, since that dependence may affect the predictive power of these models. The results obtained with the spatial regression models were also compared with the results of a multiple linear regression model that is typically used in trips generation estimations. The findings support the hypothesis that the inclusion of spatial effects in regression models is important, since the best results were obtained with alternative models (spatial regression models or the ones with spatial variables included). This was observed in a case study carried out in the city of Porto Alegre, in the state of Rio Grande do Sul, Brazil, in the stages of specification and calibration of the models, with two distinct datasets.