951 resultados para Non-Linear Elliptic Systems
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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The accurate identification of the nitrogen content in plants is extremely important since it involves economic aspects and environmental impacts, Several experimental tests have been carried out to obtain characteristics and parameters associated with the health of plants and its growing. The nitrogen content identification in plants involves a lot of non-linear parameters and complexes mathematical models. This paper describes a novel approach for identification of nitrogen content thought SPAD index using artificial neural networks (ANN). The network acts as identifier of relationships among, crop varieties, fertilizer treatments, type of leaf and nitrogen content in the plants (target). So, nitrogen content can be generalized and estimated and from an input parameter set. This approach can form the basis for development of an accurate real time system to predict nitrogen content in plants.
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Economic dispatch (ED) problems have recently been solved by artificial neural network approaches. Systems based on artificial neural networks have high computational rates due to the use of a massive number of simple processing elements and the high degree of connectivity between these elements. The ability of neural networks to realize some complex non-linear function makes them attractive for system optimization. All ED models solved by neural approaches described in the literature fail to represent the transmission system. Therefore, such procedures may calculate dispatch policies, which do not take into account important active power constraints. Another drawback pointed out in the literature is that some of the neural approaches fail to converge efficiently toward feasible equilibrium points. A modified Hopfield approach designed to solve ED problems with transmission system representation is presented in this paper. The transmission system is represented through linear load flow equations and constraints on active power flows. The internal parameters of such modified Hopfield networks are computed using the valid-subspace technique. These parameters guarantee the network convergence to feasible equilibrium points, which represent the solution for the ED problem. Simulation results and a sensitivity analysis involving IEEE 14-bus test system are presented to illustrate efficiency of the proposed approach. (C) 2004 Elsevier Ltd. All rights reserved.
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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The non-ohmic and dielectric properties as well as the dependence on the microstructural features of CaCu(3)Ti(4)O(12)/CaTiO(3) ceramic composites obtained by conventional and microwave sintering were investigated. It was demonstrated that the non-ohmic and dielectric properties depend strongly on the sintering conditions. It was found that the non-linear coefficient reaches values of 65 for microwave-sintered samples and 42 for samples sintered in a conventional furnace when a current density interval of 1-10 mA cm(-2) is considered. The non-linear coefficient value of 65 is equivalent to 1500 for samples sintered in the microwave if a current interval of 5-30 mA is considered as is shortly discussed by Chung et al (2004 Nature Mater. 3 774). Due to a high non-linear coefficient and a low leakage current (90 mu A) under both processing conditions, these samples are promising for varistor applications. The conventionally sintered samples exhibit a higher relative dielectric constant at 1 kHz (2960) compared with the samples sintered in the microwave furnace (2100). At high frequencies, the dielectric constant is also larger in the samples sintered in the conventional furnace. Depending on the application, one or another synthesis methodology is recommended, that is, for varistor applications sintered in a microwave furnace and for dielectric application sintered in a conventional furnace.
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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The objective of this paper is the numerical study of the behavior of reinforced concrete beams and columns by non-linear numerical simulations. The numerical analysis is based on the finite element method implemented in CASTEM 2000. This program uses the constitutive elastoplastic perfect model for the steel, the Drucker-Prager model for the concrete and the Newton-Raphson for the solution of non-linear systems. This work concentrates on the determination of equilibrium curves to the beams and force-strain curves to the columns. The numeric responses are confronted with experimental results found in the literature in order to check there liability of the numerical analyses.
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This paper presents a pole placement method using both the augmented Jacobian and the corresponding system transfer function matrices. From the manipulation of these matrices a straightforward approach results to get the coefficients of a non-linear system, whose solution gives the parameters of the stabilizers that can provide a pre-specified minimum damping to the system. (C) 2001 Elsevier B.V. Ltd. All rights reserved.
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Relaxed conditions for stability of nonlinear continuous-time systems given by fuzzy models axe presented. A theoretical analysis shows that the proposed method provides better or at least the same results of the methods presented in the literature. Digital simulations exemplify this fact. This result is also used for fuzzy regulators design. The nonlinear systems are represented by fuzzy models proposed by Takagi and Sugeno. The stability analysis and the design of controllers axe described by LMIs (Linear Matrix Inequalities), that can be solved efficiently using convex programming techniques.
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In this work, the quantitative analysis of glucose, triglycerides and cholesterol (total and HDL) in both rat and human blood plasma was performed without any kind of pretreatment of samples, by using near infrared spectroscopy (NIR) combined with multivariate methods. For this purpose, different techniques and algorithms used to pre-process data, to select variables and to build multivariate regression models were compared between each other, such as partial least squares regression (PLS), non linear regression by artificial neural networks, interval partial least squares regression (iPLS), genetic algorithm (GA), successive projections algorithm (SPA), amongst others. Related to the determinations of rat blood plasma samples, the variables selection algorithms showed satisfactory results both for the correlation coefficients (R²) and for the values of root mean square error of prediction (RMSEP) for the three analytes, especially for triglycerides and cholesterol-HDL. The RMSEP values for glucose, triglycerides and cholesterol-HDL obtained through the best PLS model were 6.08, 16.07 e 2.03 mg dL-1, respectively. In the other case, for the determinations in human blood plasma, the predictions obtained by the PLS models provided unsatisfactory results with non linear tendency and presence of bias. Then, the ANN regression was applied as an alternative to PLS, considering its ability of modeling data from non linear systems. The root mean square error of monitoring (RMSEM) for glucose, triglycerides and total cholesterol, for the best ANN models, were 13.20, 10.31 e 12.35 mg dL-1, respectively. Statistical tests (F and t) suggest that NIR spectroscopy combined with multivariate regression methods (PLS and ANN) are capable to quantify the analytes (glucose, triglycerides and cholesterol) even when they are present in highly complex biological fluids, such as blood plasma
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Due to its physico-chemical and biological properties, related to the abundance and low cost of raw material, chitosan has been recognized as a material of wide application in various fields, such as in drug delivery systems. Many of these properties are associated with the presence of amino groups in its polymer chain. A proper determination of these amino groups is very important, in order to properly specify if a given chitosan sample can be used in a particular application. Thus, in this work, initially, a comparison between the determination of the deacetylation degree by conductometry and elemental analysis was carried out using a detailed analysis of error propagation. It was shown that the conductometric analysis resulted in a simple and safe method for the determining the degree of deacetylation of chitosan. Subsequently, experiments were performed to monitor and characterize the adsorption of tetracycline on chitosan particles through kinetic and equilibrium studies. The main models of kinetics and adsorption isotherms, widely used to describe the adsorption on wastewater treatment systems and the drug loading, were used to treat the experimental data. Firstly, it was shown that an apparent linear t/q(t) × t relationship did not imply in a pseudo-second-order adsorption kinetics, differently of what has been repeatedly reported in the literature. It was found that this misinterpretation can be avoided by using non-linear regression. Finally, the adsorption of tetracycline on chitosan particles was analyzed using insights obtained from theoretical analysis, and the parameters generated were used to analyze the kinetics of adsorption, the isotherm of adsorption and to ropose a mechanism of adsorption
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This work an algorithm for fault location is proposed. It contains the following functions: fault detection, fault classification and fault location. Mathematical Morphology is used to process currents obtained in the monitored terminals. Unlike Fourier and Wavelet transforms that are usually applied to fault location, the Mathematical Morphology is a non-linear operation that uses only basic operation (sum, subtraction, maximum and minimum). Thus, Mathematical Morphology is computationally very efficient. For detection and classification functions, the Morphological Wavelet was used. On fault location module the Multiresolution Morphological Gradient was used to detect the traveling waves and their polarities. Hence, recorded the arrival in the two first traveling waves incident at the measured terminal and knowing the velocity of propagation, pinpoint the fault location can be estimated. The algorithm was applied in a 440 kV power transmission system, simulated on ATP. Several fault conditions where studied and the following parameters were evaluated: fault location, fault type, fault resistance, fault inception angle, noise level and sampling rate. The results show that the application of Mathematical Morphology in faults location is very promising
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This paper is a study on the population dynamics of blowflies employing a density-dependent. non-linear mathematical model and a coupled population formalism. In this Study, we investigated the coupled population dynamics applying fuzzy subsets to model the Population trajectory. analyzing demographic parameters such as fecundity, Survival, and migration. The main results suggest different possibilities in terms of dynamic behavior produced by migration in coupled Populations between distinct environments and the rescue effect generated by the connection between populations. It was possible to conclude that environmental heterogeneity can play an important role in blowfly metapopulation systems. The implications of these results for population dynamics of blowflies are discussed.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)