1000 resultados para Algoritmos - desenvolvimento
Resumo:
Técnicas de otimização conhecidas como as metaheurísticas tem conseguido resolversatisfatoriamente problemas conhecidos, mas desenvolvimento das metaheurísticas écaracterizado por escolha de parâmetros para sua execução, na qual a opção apropriadadestes parâmetros (valores). Onde o ajuste de parâmetro é essencial testa-se os parâmetrosaté que resultados viáveis sejam obtidos, normalmente feita pelo desenvolvedor que estaimplementando a metaheuristica. A qualidade dos resultados de uma instância1 de testenão será transferida para outras instâncias a serem testadas e seu feedback pode requererum processo lento de “tentativa e erro” onde o algoritmo têm que ser ajustado para umaaplicação especifica. Diante deste contexto das metaheurísticas surgiu a Busca Reativaque defende a integração entre o aprendizado de máquina dentro de buscas heurísticaspara solucionar problemas de otimização complexos. A partir da integração que a BuscaReativa propõe entre o aprendizado de máquina e as metaheurísticas, surgiu a ideia dese colocar a Aprendizagem por Reforço mais especificamente o algoritmo Q-learning deforma reativa, para selecionar qual busca local é a mais indicada em determinado instanteda busca, para suceder uma outra busca local que não pode mais melhorar a soluçãocorrente na metaheurística VNS. Assim, neste trabalho propomos uma implementação reativa,utilizando aprendizado por reforço para o auto-tuning do algoritmo implementado,aplicado ao problema do caixeiro viajante simétrico e ao problema escalonamento sondaspara manutenção de poços.
Resumo:
The Quadratic Minimum Spanning Tree (QMST) problem is a generalization of the Minimum Spanning Tree problem in which, beyond linear costs associated to each edge, quadratic costs associated to each pair of edges must be considered. The quadratic costs are due to interaction costs between the edges. When interactions occur between adjacent edges only, the problem is named Adjacent Only Quadratic Minimum Spanning Tree (AQMST). Both QMST and AQMST are NP-hard and model a number of real world applications involving infrastructure networks design. Linear and quadratic costs are summed in the mono-objective versions of the problems. However, real world applications often deal with conflicting objectives. In those cases, considering linear and quadratic costs separately is more appropriate and multi-objective optimization provides a more realistic modelling. Exact and heuristic algorithms are investigated in this work for the Bi-objective Adjacent Only Quadratic Spanning Tree Problem. The following techniques are proposed: backtracking, branch-and-bound, Pareto Local Search, Greedy Randomized Adaptive Search Procedure, Simulated Annealing, NSGA-II, Transgenetic Algorithm, Particle Swarm Optimization and a hybridization of the Transgenetic Algorithm with the MOEA-D technique. Pareto compliant quality indicators are used to compare the algorithms on a set of benchmark instances proposed in literature.
Resumo:
The Quadratic Minimum Spanning Tree (QMST) problem is a generalization of the Minimum Spanning Tree problem in which, beyond linear costs associated to each edge, quadratic costs associated to each pair of edges must be considered. The quadratic costs are due to interaction costs between the edges. When interactions occur between adjacent edges only, the problem is named Adjacent Only Quadratic Minimum Spanning Tree (AQMST). Both QMST and AQMST are NP-hard and model a number of real world applications involving infrastructure networks design. Linear and quadratic costs are summed in the mono-objective versions of the problems. However, real world applications often deal with conflicting objectives. In those cases, considering linear and quadratic costs separately is more appropriate and multi-objective optimization provides a more realistic modelling. Exact and heuristic algorithms are investigated in this work for the Bi-objective Adjacent Only Quadratic Spanning Tree Problem. The following techniques are proposed: backtracking, branch-and-bound, Pareto Local Search, Greedy Randomized Adaptive Search Procedure, Simulated Annealing, NSGA-II, Transgenetic Algorithm, Particle Swarm Optimization and a hybridization of the Transgenetic Algorithm with the MOEA-D technique. Pareto compliant quality indicators are used to compare the algorithms on a set of benchmark instances proposed in literature.
Resumo:
Atualmente o sector industrial está inserido num mercado cada vez mais competitivo, onde é exigida uma estratégia empresarial que possa garantir a sua permanência e destaque no atual mercado. Por esta razão, um planeamento e controlo da produção adequado torna-se essencial para o bom funcionamento de uma empresa. Através destes sistemas é possível atuar de forma positiva na produção, rentabilizando-se o sector produtivo da empresa que contribui para o aumento da qualidade de serviço e também para o crescimento económico da empresa. Com um planeamento da produção adequado, uma organização dispondo das mesmas capacidades, é capaz de produzir quantidades iguais num menor intervalo de tempo. Por outro lado, um controlo da produção preciso é imprescindível para o fornecimento da informação correta quando necessária. No sentido de otimização, uma empresa apresentou algumas sugestões de melhoria a nível do planeamento e controlo da produção. Este trabalho surge assim com o intuito de dar resposta às propostas apresentadas. Para tal, no desenvolvimento desta dissertação, criou-se uma ferramenta dotada de dois algoritmos e um sistema de controlo para aquisição de informação de forma automatizada. Em suma, o sistema proposto apresenta a capacidade de construção de boas soluções para o planeamento, conciliada com um sistema de aquisição de dados bastante prático e e caz. Mantendo sempre a exibilidade necessária para um sistema deste género.
Resumo:
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
Resumo:
This reaserch analysed the developmental stage of fourth grade (primary school) children in ability of writting argumentative texts joint with their context. The reason of this reaserch is the lack of new studies in linguistical area and high ratio of unable students to make this kind of text. It will be showed the analysis of making text by public schools children for three months. These data were analysed trying identify argumentative operators, the kinds of arguments used and the stage of the argumentative ability of these children. The study showed that the introduction of argumentative text in first grades give them more chances of succeed, preparing these pupils in their finishing high school. This fact obviously will make easier the development of their critical point of view, helping the students to think about their living social reality.
Resumo:
The aim of this paper is the description of the strategies and advances in the use of MIP in the development of chemical sensors. MIP has been considered an emerging technology, which allows the synthesis of materials that can mimic some highly specific natural receptors such as antibodies and enzymes. In recent years a great number of publications have demonstrated a growth in their use as sensing phases in the construction of sensors . Thus, the MIP technology became very attractive as a promising analytical tool for the development of sensors.
Resumo:
Fundamental aspects of the conception and applications of ecomaterials, in particular porous materials in the perspective of green chemistry are discussed in this paper. General recommendations for description and classification of porous materials are reviewed briefly. By way of illustration, some case studies of materials design and applications in pollution detection and remediation are described. It is shown here how different materials developed by our groups, such as porous glasses, ecomaterials from biomass and anionic clays were programmed to perform specific functions. A discussion of the present and future of ecomaterials in green chemistry is presented along with important key goals.
Resumo:
In this paper we describe the preparation poly (L-lactide) (PLA) nanocapsules as a drug delivery system for the local anesthetic benzocaine. The characterization and in vitro release properties of the system were investigated. The characterization results showed a polydispersity index of 0.14, an average diameter of 190.1± 3 nm, zeta potential of -38.5 mV and an entrapment efficiency of 73%. The release profile of Benzocaine loaded in PLA nanocapsules showed a significant different behavior than that of the pure anesthetic in solution. This study is important to characterize a drug release system using benzocaine for application in pain treatment.
Resumo:
Raman imaging spectroscopy is a highly useful analytical tool that provides spatial and spectral information on a sample. However, CCD detectors used in dispersive instruments present the drawback of being sensitive to cosmic rays, giving rise to spikes in Raman spectra. Spikes influence variance structures and must be removed prior to the use of multivariate techniques. A new algorithm for correction of spikes in Raman imaging was developed using an approach based on comparison of nearest neighbor pixels. The algorithm showed characteristics including simplicity, rapidity, selectivity and high quality in spike removal from hyperspectral images.
Resumo:
Poorly soluble drugs have low bioavailability, representing a major challenge for the pharmaceutical industry. Processing drugs into the nanosized range changes their physical properties, and these are being used in pharmaceutics to develop innovative formulations known as Nanocrystals. Use of nanocrystals to overcome the problem of low bioavailability, and their production using different techniques such as microfluidization or high pressure homogenization, was reviewed in this paper. Examples of drugs, cosmetics and nutraceutical ingredients were also discussed. These technologies are well established in the pharmaceutical industry and are approved by the Food and Drug Administration.
Resumo:
A simple analytical method for extraction and quantification of lutein colorant added to yogurt was developed and validated. The method allowed complete extraction of carotenoids using tetrahydrofuran in vortex, followed by centrifugation, partition to diethyl ether/petroleum ether, and drying. The carotenoids dissolved in ethanol were quantified by UV-Vis spectrophotometry. This method showed linearity in the range tested (1.41-13.42 µg g-1), limits of detection and quantification of 0.42 and 1.28 µg g-1, respectively, low relative standard deviation (3.4%) and recovery ranging from 95 to 103%. The method proved reliable for quantification of lutein added to yogurt.
Resumo:
Remotely sensed imagery has been widely used for land use/cover classification thanks to the periodic data acquisition and the widespread use of digital image processing systems offering a wide range of classification algorithms. The aim of this work was to evaluate some of the most commonly used supervised and unsupervised classification algorithms under different landscape patterns found in Rondônia, including (1) areas of mid-size farms, (2) fish-bone settlements and (3) a gradient of forest and Cerrado (Brazilian savannah). Comparison with a reference map based on the kappa statistics resulted in good to superior indicators (best results - K-means: k=0.68; k=0.77; k=0.64 and MaxVer: k=0.71; k=0.89; k=0.70 respectively for three areas mentioned). Results show that choosing a specific algorithm requires to take into account both its capacity to discriminate among various spectral signatures under different landscape patterns as well as a cost/benefit analysis considering the different steps performed by the operator performing a land cover/use map. it is suggested that a more systematic assessment of several options of implementation of a specific project is needed prior to beginning a land use/cover mapping job.
Resumo:
The present work aimed the development of a low cost servo-valve that answers to an electronic control signal, for variable rates liquid inputs application. A literature research to define which valve type should be used was made. A mechanically activated proportional valve with an electronically controlled servo-engine was designed and evaluated. Since developed the servo-valve, the system was submited to a number of tests .The evaluation of its behavior was obtained in terms of repeatability, hystheresis and linearity. The test was accomplished in a bench, specially developed for this aim. As a result, were obtained three curves of opening percentage as function of flow rate, describing three opening and closing increments in two different work pressures. The servo-valve presented a good repeatability, reasonable hysteresis and a typically quadratic curve. This one maintained the low cost target. These results were very satisfied because the non-linearity and the hysteresis could be easily corrected by software.
Resumo:
The objective of this work was to compare the soybean crop mapping in the western of Parana State by MODIS/Terra and TM/Landsat 5 images. Firstly, it was generated a soybean crop mask using six TM images covering the crop season, which was used as a reference. The images were submitted to Parallelepiped and Maximum Likelihood digital classification algorithms, followed by visual inspection. Four MODIS images, covering the vegetative peak, were classified using the Parallelepiped method. The quality assessment of MODIS and TM classification was carried out through an Error Matrix, considering 100 sample points between soybean or not soybean, randomly allocated in each of the eight municipalities within the study area. The results showed that both the Overall Classification (OC) and the Kappa Index (KI) have produced values ranging from 0.55 to 0.80, considered good to very good performances, either in TM or MODIS images. When OC and KI, from both sensors were compared, it wasn't found no statistical difference between them. The soybean mapping, using MODIS, has produced 70% of reliance in terms of users. The main conclusion is that the mapping of soybean by MODIS is feasible, with the advantage to have better temporal resolution than Landsat, and to be available on the internet, free of charge.