177 resultados para Algoritmo evolucionário
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In the past 50 years, large efforts have been made toward the understanding of the stellar evolution. In the observational context, large sets of precise measurements of projected rotational velocity were produced, in particular by the Natal and Geneva groups. From these data, it is now possible to establish the behavior of stellar rotation from the turnoff to the red giant branch. In addition, these data have shown the role of tidal effects on stellar rotation in close binary systems. Nevertheless, relatively little attention has been paid to theoretical studies on the evolution of rotation along the HR Diagram, a topic itself directly associated to the evolution of the stars. Basically, there are two reasons for such a fact, (i) spherical symmetry is not assumed, what leads to a substantial increase in the numerical complexity of equations and (ii) non rotating models have been very successful in explaining relevant observational data, including the mass-luminosity relation and chemical abundances. In spite of these facts, it is clear that considerable work remains to be done on the role of rotation in the later stages of the evolution, where clear disagreements arise from confrontations between theoretical predictions and observations. In the present work we study the evolutionary behavior of stellar rotation along the HR Diagram, taking into account constraint conditions issued from recent observational survey of rotational velocity carried out with high precision procedures and new evolutionary codes
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Different studies point for an rotation age link following a
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In this work we study a connection between a non-Gaussian statistics, the Kaniadakis
statistics, and Complex Networks. We show that the degree distribution P(k)of
a scale free-network, can be calculated using a maximization of information entropy in
the context of non-gaussian statistics. As an example, a numerical analysis based on the
preferential attachment growth model is discussed, as well as a numerical behavior of
the Kaniadakis and Tsallis degree distribution is compared. We also analyze the diffusive
epidemic process (DEP) on a regular lattice one-dimensional. The model is composed
of A (healthy) and B (sick) species that independently diffusive on lattice with diffusion
rates DA and DB for which the probabilistic dynamical rule A + B → 2B and B → A. This
model belongs to the category of non-equilibrium systems with an absorbing state and a
phase transition between active an inactive states. We investigate the critical behavior of
the DEP using an auto-adaptive algorithm to find critical points: the method of automatic
searching for critical points (MASCP). We compare our results with the literature and we
find that the MASCP successfully finds the critical exponents 1/ѵ and 1/zѵ in all the cases
DA =DB, DA
Sobre a relação entre rotação, atividade crosmosférica e abundância de lítio em estrelas subgigantes
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
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In this thesis we deal with a class of composed networks that are formed by two tree networks, TP and TA, whose end points touches each other through a bipartite network BPA. We explore this network using a functional approach. We are interested in what extend the topology, or the structure, of TX (X = A or P) determines the links of BPA. This composed structure is an useful model in evolutionary biology, where TP and TA are the phylogenetic trees of plants and animals that interact in an ecological community. We use in this thesis two cases of mutualist interactions: frugivory and pollinator networks. We analyse how the phylogeny of TX determines or is correlated with BPA using a Monte Carlo approach. We use the phylogenetic distance among elements that interact with a given species to construct an index κ that quantifies the influence of TX over BPA. The algorithm is based in the assumption that interaction matrices that follows a phylogeny of TX have a total phylogenetic distance smaller than the average distance of an ensemble of Monte Carlo realizations generated by an adequate shuffling data. We find that the phylogeny of animals species has an effect on the ecological matrix that is more marked than plant phylogeny
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The study physical process that control the stellar evolution is strength influenced by several stellar parameters, like as rotational velocity, convective envelope mass deepening, and magnetic field intensity. In this study we analyzed the interconnection of some stellar parameters, as Lithium abundance A(Li), chromospheric activity and magnetic field intensity as well as the variation of these parameters as a function of age, rotational velocity, and the convective envelope mass deepening for a selected sample of solar analogs and twins stars. In particular, we analyzed the convective envelope mass deepening and the dispersion of lithium abundance for these stars. We also studied the evolution of rotation in subgiants stars, because its belong to the following evolutionary stage of solar analogs, and twins stars. For this analyze, we compute evolutionary models with the TGEC code to derive the evolutionary stage, as well as the convective envelope mass deepening, and derive more precisely the stellar mass, and age for this 118 stars. Our Investigation shows a considerable dispersion of lithium abundance for the solar analogs stars. We also realize that this dispersion is not by the convective zone deep, in this way we observed which the scattering of A(Li) can not be explained by classical theories of mixing in the convective zone. In conclusion we have that are necessary extra-mixing process to explain this decrease of Lithium abundance in solar analogs and twins stars. We analyzed the subgiant stars because this are the subsequent evolutionary stage after the solar analogs and twins stars. For this analysis, we compute the rotational period for 30 subgiants stars observed by Co- RoT satellite. For this task we apply two different methods: Lomb-Scargle algorithm, and the Plavchan Periodogram. We apply the TGEC code we compute models with internal distribution of angular momentum to confront the predict results with the models, and the observational results. With this analyze, we showed which solid body rotation models are incompatible with the physical interpretation of observational results. As a result of our study we still concluded that the magnetic field, convective envelope mass deepening, and internal redistribution of angular momentum are essential to explain the evolution of low-mass stars, and its observational characteristics. Based on population synthesis simulation, we concluded that the solar neighborhood presents a considerable quantity of solar twins when compared with the discovered set nowadays. Altogether we foresee the existence around 400 solar analogs in the solar neighborhood (distance of 100 pc). We also study the angular momentum of solar analogs and twins, in this study we concluded that added angular momentum from a Jupiter type planet, putted in the Jupiter position, is not enough to explain the angular momentum predicted by Kraft law (Kraft 1970)
Sobre a relação entre rotação, atividade crosmosférica e abundância de lítio em estrelas subgigantes
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The connection between rotation, CaII emission flux and lithium abundance is analyzed for a sample of subgiant stars, with evolutionary status was determined from the Toulouse-Geneve code and HlPPARCOS trigonometric parallax measurements. We noted that the distribution of rotation and CaII emission flux, as a function of effective temperature, shows a discontinuity located around the same spectral type, F8IV. Stars located blueward of this spectral type, exhibit a large spread of values of rotation and CaII flux, whereas stars redward of F8lV show essentially low ratation anel low CaII flux. The strength of these declines nevertheless, depends on stellar mass. The distribution of lithium abundances also shows a discontinuity, however with behavior a little more complex for subgiants with mass lower than about 1.2 Solar Masses, this decrease is observed later than that in rotation and CaII flux, whereas for masses higher than 1.2 Solar Masses the decrease in lithium abundance is located around the spectral type F8IV. The discrepancy between the location of the discontinuities of rotation and CaII flux and log n(Li) for stars with masses lower than 102 Solar Masses, seems to reflect the sensitivity of these phenomena to the mass of the convective envelope. The drop in rotation, which results mostly from a magnetic braking, requires an increase in the mass of the convective envelope less than that required for the decrease in lithium abundance The location of the discontinuity in log n( Li) in the same region of the discontinuity ties in rotation and CaII flux, for stars with masses higher than 1.2 Solar Masses, may also be explained by the behavior of the deepening of the convective envelope. In contrast to the relationship between rotation and CaII flux the relationship between lithium abundance and rotation shows no dear tendency toward linear behavior. Similarly, the same tendency is observed in the relationship between lithium abundance and CaII flux in spite of these facts, subgiants with high lithium content also have high rotation and high CaII emission flux. We also observed that stars with high lithium content present, in its majority, an undeveloped convective envelope, whereas stars with low lithium content have a developed convective envelope. In the case of the rotation, stars with undeveloped convective envelope, show rotational velocities as much high as low, whereas stars with developed convective envelope only present low rotation
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In this work, we study and compare two percolation algorithms, one of then elaborated by Elias, and the other one by Newman and Ziff, using theorical tools of algorithms complexity and another algorithm that makes an experimental comparation. This work is divided in three chapters. The first one approaches some necessary definitions and theorems to a more formal mathematical study of percolation. The second presents technics that were used for the estimative calculation of the algorithms complexity, are they: worse case, better case e average case. We use the technique of the worse case to estimate the complexity of both algorithms and thus we can compare them. The last chapter shows several characteristics of each one of the algorithms and through the theoretical estimate of the complexity and the comparison between the execution time of the most important part of each one, we can compare these important algorithms that simulate the percolation.
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In this work we presented an exhibition of the mathematical theory of orthogonal compact support wavelets in the context of multiresoluction analysis. These are particularly attractive wavelets because they lead to a stable and very efficient algorithm, that is Fast Transform Wavelet (FWT). One of our objectives is to develop efficient algorithms for calculating the coefficients wavelet (FWT) through the pyramid algorithm of Mallat and to discuss his connection with filters Banks. We also studied the concept of multiresoluction analysis, that is the context in that wavelets can be understood and built naturally, taking an important step in the change from the Mathematical universe (Continuous Domain) for the Universe of the representation (Discret Domain)
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In this work we study the survival cure rate model proposed by Yakovlev (1993) that are considered in a competing risk setting. Covariates are introduced for modeling the cure rate and we allow some covariates to have missing values. We consider only the cases by which the missing covariates are categorical and implement the EM algorithm via the method of weights for maximum likelihood estimation. We present a Monte Carlo simulation experiment to compare the properties of the estimators based on this method with those estimators under the complete case scenario. We also evaluate, in this experiment, the impact in the parameter estimates when we increase the proportion of immune and censored individuals among the not immune one. We demonstrate the proposed methodology with a real data set involving the time until the graduation for the undergraduate course of Statistics of the Universidade Federal do Rio Grande do Norte
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In this work we have elaborated a spline-based method of solution of inicial value problems involving ordinary differential equations, with emphasis on linear equations. The method can be seen as an alternative for the traditional solvers such as Runge-Kutta, and avoids root calculations in the linear time invariant case. The method is then applied on a central problem of control theory, namely, the step response problem for linear EDOs with possibly varying coefficients, where root calculations do not apply. We have implemented an efficient algorithm which uses exclusively matrix-vector operations. The working interval (till the settling time) was determined through a calculation of the least stable mode using a modified power method. Several variants of the method have been compared by simulation. For general linear problems with fine grid, the proposed method compares favorably with the Euler method. In the time invariant case, where the alternative is root calculation, we have indications that the proposed method is competitive for equations of sifficiently high order.
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This paper we study a random strategy called MOSES, which was introduced in 1996 by Fran¸cois. Asymptotic results of this strategy; behavior of the stationary distributions of the chain associated to strategy, were derived by Fran¸cois, in 1998, of the theory of Freidlin and Wentzell [8]. Detailings of these results are in this work. Moreover, we noted that an alternative approach the convergence of this strategy is possible without making use of theory of Freidlin and Wentzell, yielding the visit almost certain of the strategy to uniform populations which contain the minimum. Some simulations in Matlab are presented in this work
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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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The aim of this study was to evaluate the potential of near-infrared reflectance spectroscopy (NIRS) as a rapid and non-destructive method to determine the soluble solid content (SSC), pH and titratable acidity of intact plums. Samples of plum with a total solids content ranging from 5.7 to 15%, pH from 2.72 to 3.84 and titratable acidity from 0.88 a 3.6% were collected from supermarkets in Natal-Brazil, and NIR spectra were acquired in the 714 2500 nm range. A comparison of several multivariate calibration techniques with respect to several pre-processing data and variable selection algorithms, such as interval Partial Least Squares (iPLS), genetic algorithm (GA), successive projections algorithm (SPA) and ordered predictors selection (OPS), was performed. Validation models for SSC, pH and titratable acidity had a coefficient of correlation (R) of 0.95 0.90 and 0.80, as well as a root mean square error of prediction (RMSEP) of 0.45ºBrix, 0.07 and 0.40%, respectively. From these results, it can be concluded that NIR spectroscopy can be used as a non-destructive alternative for measuring the SSC, pH and titratable acidity in plums
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The Car Rental Salesman Problem (CaRS) is a variant of the classical Traveling Salesman Problem which was not described in the literature where a tour of visits can be decomposed into contiguous paths that may be performed in different rental cars. The aim is to determine the Hamiltonian cycle that results in a final minimum cost, considering the cost of the route added to the cost of an expected penalty paid for each exchange of vehicles on the route. This penalty is due to the return of the car dropped to the base. This paper introduces the general problem and illustrates some examples, also featuring some of its associated variants. An overview of the complexity of this combinatorial problem is also outlined, to justify their classification in the NPhard class. A database of instances for the problem is presented, describing the methodology of its constitution. The presented problem is also the subject of a study based on experimental algorithmic implementation of six metaheuristic solutions, representing adaptations of the best of state-of-the-art heuristic programming. New neighborhoods, construction procedures, search operators, evolutionary agents, cooperation by multi-pheromone are created for this problem. Furtermore, computational experiments and comparative performance tests are conducted on a sample of 60 instances of the created database, aiming to offer a algorithm with an efficient solution for this problem. These results will illustrate the best performance reached by the transgenetic algorithm in all instances of the dataset