949 resultados para Mathematical modelling


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Eutrophication has been listed as one of the main problems of water pollution on a global level. In the Brazilian semi-arid areas this problem takes even greater proportions due to characteristical water scarcity of the region. It is extremely important to the predictive eutrophication models development and to the reservoirs management in the semi-arid region, studies that promotes understanding of the mechanisms responsible for the expansion and control of algae blooms, essential for improving the water quality of these environments. The present study had as its main aims, evaluate the temporal pattern of trophic state, considering the influence of nutrients (N and P) and the light availability in the water column in the development of phytoplankton biomass, and perform the mathematical modelling of changes in phosphorus and chlorophyll a concentrations in the Cruzeta man-made lake located on Seridó, a typical semi-arid region of Rio Grande do Norte. To this, a fortnightly monitoring was performed in the reservoir in 05 stations over the months of March 2007 to May 2008. Were measured the concentrations of total phosphorus, total organic nitrogen, chlorophyll a, total, fixed and volatile suspended solids, as well as the measure of transparency (Secchi) and the profiles of photosynthetic active radiation (PAR), temperature, pH, dissolved oxygen and electrical conductivity in the water column. Measurements of vertical profiles have shown some periods of chemical and thermal stratification, especially in the rainy season, due to increased water column depth, however, the reservoir can be classified as warm polimitic. During the study period the reservoir was characterized as eutrophic considering the concentrations of phosphorus and most of the time as mesotrophic, based on the concentrations of chlorophyll a, according to the Thornton & Rast (1993) classification. The N:P relations suggest N limitation, conversely, significant linear relationship between the algae biomass and nutrients (N and P) were not observed in our study. However, a relevant event was the negative and significant correlation presented by Kt and chlorophyll a (r ² = 0.83) at the end of the drought of 2007 and the rainy season of 2008, and the algal biomass collapse observed at the end of the drought season (Dec/07). The equation used to simulate the change in the total phosphorus was not satisfactory, being necessary inclusion of parameters able to increase the power of the model prediction. The chlorophyll a simulation presented a good adjustment trend, however there is a need to check the calibrated model parameters and subsequent equation validation

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This paper presents an efficient approach based on recurrent neural network for solving nonlinear optimization. More specifically, a modified Hopfield network is developed and its internal parameters are computed using the valid subspace technique. These parameters guarantee the convergence of the network to the equilibrium points that represent an optimal feasible solution. The main advantage of the developed network is that it treats optimization and constraint terms in different stages with no interference with each other. Moreover, the proposed approach does not require specification of penalty and weighting parameters for its initialization. A study of the modified Hopfield model is also developed to analyze its stability and convergence. Simulation results are provided to demonstrate the performance of the proposed neural network. (c) 2005 Elsevier B.V. All rights reserved.

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The dengue virus is an arbovirus transmitted to humans through mosquito Aedes aegypti. To describe the dynamics of dengue disease within these two populations we develop a compartment model taking into account chemical controls and mechanical control applied on the mosquitoes, which are the currently available controlling mechanisms to prevent dengue disease. To mimic seasonal variations, some parameters of the model are allowed to depend on time in order to divide a calendar year in favorable and unfavorable periods regarded to the development of vector population. (c) 2007 Elsevier B.V. All rights reserved.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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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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A methodology of identification and characterization of coherent structures mostly known as clusters is applied to hydrodynamic results of numerical simulation generated for the riser of a circulating fluidized bed. The numerical simulation is performed using the MICEFLOW code, which includes the two-fluids IIT's hydrodynamic model B. The methodology for cluster characterization that is used is based in the determination of four characteristics, related to average life time, average volumetric fraction of solid, existing time fraction and frequency of occurrence. The identification of clusters is performed by applying a criterion related to the time average value of the volumetric solid fraction. A qualitative rather than quantitative analysis is performed mainly owing to the unavailability of operational data used in the considered experiments. Concerning qualitative analysis, the simulation results are in good agreement with literature. Some quantitative comparisons between predictions and experiment were also presented to emphasize the capability of the modeling procedure regarding the analysis of macroscopic scale coherent structures. (c) 2007 Elsevier B.V. All rights reserved.

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Goal Programming (GP) is an important analytical approach devised to solve many realworld problems. The first GP model is known as Weighted Goal Programming (WGP). However, Multi-Choice Aspirations Level (MCAL) problems cannot be solved by current GP techniques. In this paper, we propose a Multi-Choice Mixed Integer Goal Programming model (MCMI-GP) for the aggregate production planning of a Brazilian sugar and ethanol milling company. The MC-MIGP model was based on traditional selection and process methods for the design of lots, representing the production system of sugar, alcohol, molasses and derivatives. The research covers decisions on the agricultural and cutting stages, sugarcane loading and transportation by suppliers and, especially, energy cogeneration decisions; that is, the choice of production process, including storage stages and distribution. The MCMIGP allows decision-makers to set multiple aspiration levels for their problems in which the more/higher, the better and the less/lower, the better in the aspiration levels are addressed. An application of the proposed model for real problems in a Brazilian sugar and ethanol mill was conducted; producing interesting results that are herein reported and commented upon. Also, it was made a comparison between MCMI GP and WGP models using these real cases. © 2013 Elsevier Inc.

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Pós-graduação em Ciências Biológicas (Biologia Vegetal) - IBRC

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Pós-graduação em Biometria - IBB

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Pós-graduação em Educação Matemática - IGCE

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Pós-graduação em Educação Matemática - IGCE

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Pós-graduação em Ciência Animal - FMVA

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Pós-graduação em Educação Matemática - IGCE