Seleção de características utilizando algoritmos evolucionistas e suas aplicações em reconhecimento de padrões

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Harmony Search applied for Support Vector Machines Training Optimization

Since the beginning, some pattern recognition techniques have faced the problem of high computational burden for dataset learning. Among the most widely used techniques, we may highlight Support Vector Machines (SVM), which have obtained very promising results for data classification. However, this classifier requires an expensive training phase, which is dominated by a parameter optimization that aims to make SVM less prone to errors over the training set. In this paper, we model the problem of finding such parameters as a metaheuristic-based optimization task, which is performed through Harmony Search (HS) and some of its variants. The experimental results have showen the robustness of HS-based approaches for such task in comparison against with an exhaustive (grid) search, and also a Particle Swarm Optimization-based implementation.

Investigação sobre deformação neotectônica no lineamento Guapiara, região de Ourinhos, Fartura-SP e Santo Antonio da Platina - PR

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Investigação sobre deformação neotectônica no lineamento Guapiara, região de Guapiara e Jacupiranga

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

On the optical flow model selection through metaheuristics

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

Evolutionary optimization applied for fine-tuning parameter estimation in optical flow-based environments

Optical flow methods are accurate algorithms for estimating the displacement and velocity fields of objects in a wide variety of applications, being their performance dependent on the configuration of a set of parameters. Since there is a lack of research that aims to automatically tune such parameters, in this work we have proposed an evolutionary-based framework for such task, thus introducing three techniques for such purpose: Particle Swarm Optimization, Harmony Search and Social-Spider Optimization. The proposed framework has been compared against with the well-known Large Displacement Optical Flow approach, obtaining the best results in three out eight image sequences provided by a public dataset. Additionally, the proposed framework can be used with any other optimization technique.

Caracterização da produção e qualidade físico-química de méis produzidos no Estado de Pernambuco

The present study had as objective contribute to the characterization of beekeeping in the Pernambuco State and evaluate the physical-chemical quality of the honeys produced in the region. For this, was applied a directed formulary to the representative organ of beekeeping class aboutthe productives and technicals aspects of beekeepers. Was obtained 14 samples of honey by Apis mellifera africanized, stored in sterile plastic vessels was sent to the Beekeeping Products Quality Control Laboratory (CEA-UNITAU). Was observed that the most of beekeepers have of 50 to 100 hives (57,14%), 28,57% of 100 to 200 hives and 14,28% more than 500 hives, being that 85,71% produce 30 to 50 kg honey/hives/flowering. All use the standard hive Langstroth and 85,71% obtain their swarm by capture. About the physical-chemical quality of the honey, was observed that moisture content varied from 18,2% to 22,0%, with mean value of 19,80±1,11; the water activity varied from 0,70 to 0,84 aw, with mean value of 0,79±0,05 aw; the total acidity was 24,91±8,99 meq/kg and the average index of hydroxymethylfurfural was 16,32±17,88 meq/kg. The results obtained are according to the quality limits established by the brazilian legislation, excepted the water activity that exceeded the maximum limit of 0,65 aw. The datasobtained in this paper shows the development of beekeeping in Pernambuco State and the honey presents nice quality.

Phylogeographic analysis in populations of Protonectarina sylveirae (Saussure, 1854) (Hymenoptera, Vespidae, Polistinae)

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