73 resultados para Cadeias de Markov. Algoritmos genéticos
Resumo:
Launching centers are designed for scientific and commercial activities with aerospace vehicles. Rockets Tracking Systems (RTS) are part of the infrastructure of these centers and they are responsible for collecting and processing the data trajectory of vehicles. Generally, Parabolic Reflector Radars (PRRs) are used in RTS. However, it is possible to use radars with antenna arrays, or Phased Arrays (PAs), so called Phased Arrays Radars (PARs). Thus, the excitation signal of each radiating element of the array can be adjusted to perform electronic control of the radiation pattern in order to improve functionality and maintenance of the system. Therefore, in the implementation and reuse projects of PARs, modeling is subject to various combinations of excitation signals, producing a complex optimization problem due to the large number of available solutions. In this case, it is possible to use offline optimization methods, such as Genetic Algorithms (GAs), to calculate the problem solutions, which are stored for online applications. Hence, the Genetic Algorithm with Maximum-Minimum Crossover (GAMMC) optimization method was used to develop the GAMMC-P algorithm that optimizes the modeling step of radiation pattern control from planar PAs. Compared with a conventional crossover GA, the GAMMC has a different approach from the conventional one, because it performs the crossover of the fittest individuals with the least fit individuals in order to enhance the genetic diversity. Thus, the GAMMC prevents premature convergence, increases population fitness and reduces the processing time. Therefore, the GAMMC-P uses a reconfigurable algorithm with multiple objectives, different coding and genetic operator MMC. The test results show that GAMMC-P reached the proposed requirements for different operating conditions of a planar RAV.
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Oil exploration at great depths requires the use of mobile robots to perform various operations such as maintenance, assembly etc. In this context, the trajectory planning and navigation study of these robots is relevant, as the great challenge is to navigate in an environment that is not fully known. The main objective is to develop a navigation algorithm to plan the path of a mobile robot that is in a given position (
Resumo:
Oil exploration at great depths requires the use of mobile robots to perform various operations such as maintenance, assembly etc. In this context, the trajectory planning and navigation study of these robots is relevant, as the great challenge is to navigate in an environment that is not fully known. The main objective is to develop a navigation algorithm to plan the path of a mobile robot that is in a given position (
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This thesis presents a hybrid technique of frequency selective surfaces project (FSS) on a isotropic dielectric layer, considering various geometries for the elements of the unit cell. Specifically, the hybrid technique uses the equivalent circuit method in conjunction with genetic algorithm, aiming at the synthesis of structures with response single-band and dual-band. The equivalent circuit method allows you to model the structure by using an equivalent circuit and also obtaining circuits for different geometries. From the obtaining of the parameters of these circuits, you can get the transmission and reflection characteristics of patterned structures. For the optimization of patterned structures, according to the desired frequency response, Matlab™ optimization tool named optimtool proved to be easy to use, allowing you to explore important results on the optimization analysis. In this thesis, numeric and experimental results are presented for the different characteristics of the analyzed geometries. For this, it was determined a technique to obtain the parameter N, which is based on genetic algorithms and differential geometry, to obtain the algebraic rational models that determine values of N more accurate, facilitating new projects of FSS with these geometries. The optimal results of N are grouped according to the occupancy factor of the cell and the thickness of the dielectric, for modeling of the structures by means of rational algebraic equations. Furthermore, for the proposed hybrid model was developed a fitness function for the purpose of calculating the error occurred in the definitions of FSS bandwidths with transmission features single band and dual band. This thesis deals with the construction of prototypes of FSS with frequency settings and band widths obtained with the use of this function. The FSS were initially reviewed through simulations performed with the commercial software Ansoft Designer ™, followed by simulation with the equivalent circuit method for obtaining a value of N in order to converge the resonance frequency and the bandwidth of the FSS analyzed, then the results obtained were compared. The methodology applied is validated with the construction and measurement of prototypes with different geometries of the cells of the arrays of FSS.
Resumo:
This thesis presents a hybrid technique of frequency selective surfaces project (FSS) on a isotropic dielectric layer, considering various geometries for the elements of the unit cell. Specifically, the hybrid technique uses the equivalent circuit method in conjunction with genetic algorithm, aiming at the synthesis of structures with response single-band and dual-band. The equivalent circuit method allows you to model the structure by using an equivalent circuit and also obtaining circuits for different geometries. From the obtaining of the parameters of these circuits, you can get the transmission and reflection characteristics of patterned structures. For the optimization of patterned structures, according to the desired frequency response, Matlab™ optimization tool named optimtool proved to be easy to use, allowing you to explore important results on the optimization analysis. In this thesis, numeric and experimental results are presented for the different characteristics of the analyzed geometries. For this, it was determined a technique to obtain the parameter N, which is based on genetic algorithms and differential geometry, to obtain the algebraic rational models that determine values of N more accurate, facilitating new projects of FSS with these geometries. The optimal results of N are grouped according to the occupancy factor of the cell and the thickness of the dielectric, for modeling of the structures by means of rational algebraic equations. Furthermore, for the proposed hybrid model was developed a fitness function for the purpose of calculating the error occurred in the definitions of FSS bandwidths with transmission features single band and dual band. This thesis deals with the construction of prototypes of FSS with frequency settings and band widths obtained with the use of this function. The FSS were initially reviewed through simulations performed with the commercial software Ansoft Designer ™, followed by simulation with the equivalent circuit method for obtaining a value of N in order to converge the resonance frequency and the bandwidth of the FSS analyzed, then the results obtained were compared. The methodology applied is validated with the construction and measurement of prototypes with different geometries of the cells of the arrays of FSS.
Resumo:
This work proposes a new autonomous navigation strategy assisted by genetic algorithm with dynamic planning for terrestrial mobile robots, called DPNA-GA (Dynamic Planning Navigation Algorithm optimized with Genetic Algorithm). The strategy was applied in environments - both static and dynamic - in which the location and shape of the obstacles is not known in advance. In each shift event, a control algorithm minimizes the distance between the robot and the object and maximizes the distance from the obstacles, rescheduling the route. Using a spatial location sensor and a set of distance sensors, the proposed navigation strategy is able to dynamically plan optimal collision-free paths. Simulations performed in different environments demonstrated that the technique provides a high degree of flexibility and robustness. For this, there were applied several variations of genetic parameters such as: crossing rate, population size, among others. Finally, the simulation results successfully demonstrate the effectiveness and robustness of DPNA-GA technique, validating it for real applications in terrestrial mobile robots.
Resumo:
This work proposes a new autonomous navigation strategy assisted by genetic algorithm with dynamic planning for terrestrial mobile robots, called DPNA-GA (Dynamic Planning Navigation Algorithm optimized with Genetic Algorithm). The strategy was applied in environments - both static and dynamic - in which the location and shape of the obstacles is not known in advance. In each shift event, a control algorithm minimizes the distance between the robot and the object and maximizes the distance from the obstacles, rescheduling the route. Using a spatial location sensor and a set of distance sensors, the proposed navigation strategy is able to dynamically plan optimal collision-free paths. Simulations performed in different environments demonstrated that the technique provides a high degree of flexibility and robustness. For this, there were applied several variations of genetic parameters such as: crossing rate, population size, among others. Finally, the simulation results successfully demonstrate the effectiveness and robustness of DPNA-GA technique, validating it for real applications in terrestrial mobile robots.
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
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The problems of combinatory optimization have involved a large number of researchers in search of approximative solutions for them, since it is generally accepted that they are unsolvable in polynomial time. Initially, these solutions were focused on heuristics. Currently, metaheuristics are used more for this task, especially those based on evolutionary algorithms. The two main contributions of this work are: the creation of what is called an -Operon- heuristic, for the construction of the information chains necessary for the implementation of transgenetic (evolutionary) algorithms, mainly using statistical methodology - the Cluster Analysis and the Principal Component Analysis; and the utilization of statistical analyses that are adequate for the evaluation of the performance of the algorithms that are developed to solve these problems. The aim of the Operon is to construct good quality dynamic information chains to promote an -intelligent- search in the space of solutions. The Traveling Salesman Problem (TSP) is intended for applications based on a transgenetic algorithmic known as ProtoG. A strategy is also proposed for the renovation of part of the chromosome population indicated by adopting a minimum limit in the coefficient of variation of the adequation function of the individuals, with calculations based on the population. Statistical methodology is used for the evaluation of the performance of four algorithms, as follows: the proposed ProtoG, two memetic algorithms and a Simulated Annealing algorithm. Three performance analyses of these algorithms are proposed. The first is accomplished through the Logistic Regression, based on the probability of finding an optimal solution for a TSP instance by the algorithm being tested. The second is accomplished through Survival Analysis, based on a probability of the time observed for its execution until an optimal solution is achieved. The third is accomplished by means of a non-parametric Analysis of Variance, considering the Percent Error of the Solution (PES) obtained by the percentage in which the solution found exceeds the best solution available in the literature. Six experiments have been conducted applied to sixty-one instances of Euclidean TSP with sizes of up to 1,655 cities. The first two experiments deal with the adjustments of four parameters used in the ProtoG algorithm in an attempt to improve its performance. The last four have been undertaken to evaluate the performance of the ProtoG in comparison to the three algorithms adopted. For these sixty-one instances, it has been concluded on the grounds of statistical tests that there is evidence that the ProtoG performs better than these three algorithms in fifty instances. In addition, for the thirty-six instances considered in the last three trials in which the performance of the algorithms was evaluated through PES, it was observed that the PES average obtained with the ProtoG was less than 1% in almost half of these instances, having reached the greatest average for one instance of 1,173 cities, with an PES average equal to 3.52%. Therefore, the ProtoG can be considered a competitive algorithm for solving the TSP, since it is not rare in the literature find PESs averages greater than 10% to be reported for instances of this size.
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In this work we study the Hidden Markov Models with finite as well as general state space. In the finite case, the forward and backward algorithms are considered and the probability of a given observed sequence is computed. Next, we use the EM algorithm to estimate the model parameters. In the general case, the kernel estimators are used and to built a sequence of estimators that converge in L1-norm to the density function of the observable process
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Background: Leprosy can cause severe disability and disfigurement and is still a major health in different parts of the world. Only a subset of those individuals exposed to the pathogen will go on to develop clinical disease and there is a broad clinical spectrum amongst leprosy patients. The outcome of infection is in part due to host genes that influence control of the initial infection and the host´s immune response to that infection. Aim: Evaluate if polymorphisms type SNP in the 17q118q21 chromosomic region contribute to development of leprosy in Rio Grande do Norte population. Material and methods: A sample composed of 215 leprosy patients and 229 controls drawn from the same population were genotyped by using a Snapshot assay for eight genes (NOS2A, CCL18, CRLF3, CCL23, TNFAIP1, STAT5B, CCR7 and CSF3) located in chromosomic region 17q118q21. The genotype and allele frequency were measured and statistical analysis was performed by chi-square in SPSS version 15 and graph prism pad version 4 software. Results: Ours results indicated that the markers NOS2A8277, NOS2A8rs16949, CCR78rs11574663 and CSF38rs2227322 presented strong association with leprosy and their risk genotype were GG, TT, AA and GG respectively. The risk genotypes for all markers associated to leprosy presented recessive inheritance standard. When we compared the interaction among the markers in different combination we find that the marker NOS2A8277 associated with CCR78rs11574663 presented highest risk probability to development of leprosy. When we evaluated the haplotype of the risk markers it was found a haplotype associated with increase of the protection (CSF38rs22273228CC, CCR78 rs115746638GA, NOS2A8rs169498CT and NOS2A82778GA). The association of the clinical forms paucibacilary and multibacilary with markers showed that to the markers NOS2A8 2778GG, CCR78rs115746638AA and CSF38rs22273228GG there were a strong influence to migration to multibacilary pole and to marker NOS2A8rs169498TT the high proportion was found to the paucibacilary form. Conclusions: Changes in the genes NOS2A, CCR7 and CSF3 can influence the immune response against Mycobacterium leprae. The combination among these polymorphisms alters the risk probability to develop leprosy. The markers type SNP associated to development of the leprosy also are linked to clinical forms and its severity being the polymorphism NOS2A8rs169498TT associated with paucibacilar form and the polymorphisms NOS2A82778GG, CCR78rs115746638AA and CSF38rs22273228GG associated to multibacilar form
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
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This master dissertation presents the study and implementation of inteligent algorithms to monitor the measurement of sensors involved in natural gas custody transfer processes. To create these algoritmhs Artificial Neural Networks are investigated because they have some particular properties, such as: learning, adaptation, prediction. A neural predictor is developed to reproduce the sensor output dynamic behavior, in such a way that its output is compared to the real sensor output. A recurrent neural network is used for this purpose, because of its ability to deal with dynamic information. The real sensor output and the estimated predictor output work as the basis for the creation of possible sensor fault detection and diagnosis strategies. Two competitive neural network architectures are investigated and their capabilities are used to classify different kinds of faults. The prediction algorithm and the fault detection classification strategies, as well as the obtained results, are presented
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The elaboration of profiles with characteristics that can be parameters in the different categories of sports modalities and the investment in scientific studies have revealed a significant importance in the development of new generations of athletes. Based in the exposed, the purpose of this study was to identify and compare the somatotype characteristics, physical qualities and genetic markers of Brazilian male volleyball players in the 14-17 category playing at different levels (international, national and regional). We used a scale, stadiometer, pachymeter, and adipometer to evaluate somatotype, attack and block reach test, medicine ball toss, 30-meter agility test , the AAHPER -30 test to evaluate basic physical qualities and the dermatoglyphic method to identify genetic markers. The results show the superiority of the national team over the other squads in the somatotype component (ectomorphy), and in the level of basic physical qualities. We found no significant difference in genetic markers among the teams studied. We conclude that Brazilian volleyball players at different performance levels have characteristics peculiar to the sport, with height and physical qualities being significantly different among these teams. The results confirm de necessity of knowing the athletes specific characteristics when dealing with high performance teams using nutrition, medicine, physiology and genetics specific knowledges to achieve a better sportive development
Resumo:
The aim of this research was to analyse genetic markers, anthropometry and basic physical qualities in the differret stages of sexual maturation in swimmers in Paraíba. It is characterised as a descriptive cross sectional study. The sample was composed of 119 swimmers (males) that were divided among the stages of sexual maturation, from 7 to 17,9 years of age. They were associated to a local federation, the Confederação Brasileira de Desportes Aquáticos. The tests used were: genetic markers dermatoglyphics; Anthropometry body mass, stature, arm span, fat percentage and somatotype; physical qualities speed tests (25 meters crawl), strength (vertical jump) to inferior limbs, verarm throwing arremesso of a 2kg medicineball to superior limbs and abdominal), resistence (12 minutes to swimming), agility (he multistage 20-meter shuttle run test), flexibility (sit and reach test ) and coodination (stroke index); power of swimming (mean velocity in 25 meters mutiplied by body mass) and the self assessment of the sexual maturation supervised by a pediatric specialist. In the analyses we used the test normality of Shapiro-Wilk, then, we used ANOVA- one way followed by Post-Hoc test of Scheffé. The data showed in dermatogliphics a genetic tendence to velocity (L>W) with a predominance of the meso-ectomorphic somatotype profile; in relation to the physical qualities there was an evolution of the results in every stage due to the antropometric variables, except in the coordination tests. There were no significative differences between the stages. We conclude that swimming in Paraíba is composed of a signicative number of velocists with a mesomorph somatotype profile and low fat percentage, and that made it posssible to us to recomend that the trainings must be individual and according to personal characteristics of each athlete, and that the used variables must be specific for every region of the country. This dissertation presents a relation of multidiciplinar interface and its content has an application in Physical Education and Medicine