Programa de Pós-graduação em Engenharia Elétrica e da Computação
URI Permanente desta comunidade
Navegar
Navegando Programa de Pós-graduação em Engenharia Elétrica e da Computação por Por Orientador "BRITO, Leonardo da Cunha"
Agora exibindo 1 - 5 de 5
Resultados por página
Opções de Ordenação
Item Descoberta automatizada de associações com o uso de algoritmo Apriori como técnica de mineração de dados(Universidade Federal de Goiás, 2011-02-25) ALMEIDA, Derciley Cunha de; BRITO, Leonardo da Cunha; http://lattes.cnpq.br/6660680440182900Nowadays, the use of modern information systems allows the storage and management of increasingly large amounts of data. On the other hand, the full analysis and the maximum extraction of useful information from this universe of available data present considerable challenges in view of inherent human limitations. This dissertation deals with the subject of data mining, which is the use of technology resources in order to extract information from databases in an automated way. One of the possibilities offered by data mining technologies is the automated search for possible associations within data. Information about such associations can be useful for understanding cause and effect relationships between the involved variables in data analysis for decision making. There are several data mining techniques and many of them can be used for discovering associations. The main goal of this work is to study a particular method for automated search of associations called Apriori , evaluating its capabilities and outcomes. The study focuses on the problem of improving the Apriori algorithm results, taking into consideration that the results of the data mining process might be improved if the data are prepared specifically for Apriori application. The conclusions are drawn from a case study in which the Apriori algorithm was applied to a database with information on drug distribution at a health institute. The results of two experiments are considered in order to evaluate the influence of data preprocessing on the Apriori algorithm's performance. It was found that the Apriori algorithm yields satisfactory results on the discovery of association in data; however, for best results, it is advisable that the data be prepared in advance, specifically for the Apriori application, otherwise many associations in the database might be left undiscovered.Item Uso de sistemas tutores inteligentes na compreensão de leitura(Universidade Federal de Goiás, 2009-11-28) BORGES, Fabrícia Neres; BRITO, Leonardo da Cunha; http://lattes.cnpq.br/6660680440182900Brazilian students have achieved poor results in the National Student Performance Exam (ENADE) in 2006. ENADE has shown reading is badly cultivated among undergraduates. The low interest on reading is justified by the fact that most of students have jobs and are enrolled in evening courses, without enough time to studies. The current research proposes the use of intelligent tutoring systems to improve student reading comprehension. The main goal is to develop the technique of underlining among undergraduates to assist in the analysis of academic texts. Two groups of students, A and B, participated in data collection. The difference between the groups is the amount of exercises performed in each group. Students of Group A have received 20 exercises with four levels of difficulty. In Group B, an Artificial Neural Network, Multilayer Perceptron (MLP), decides the amount of exercises that the student must perform at each level of difficulty by controlling what is the next exercise after each exercise is finished. The approach used in Group B adapts to the characteristics of knowledge retention of each student. Therefore, the tutoring system adapts the degree of exercise difficulty to the student. Statistical data analysis has indicated significant differences between groups A and B.Item Programação Genética Aplicada à Programação de Controladores Lógico Programáveis(Universidade Federal de Goiás, 2009-05-29) CARNEIRO, Marcos Lajovic; BRITO, Leonardo da Cunha; http://lattes.cnpq.br/6660680440182900This research proposes the application of an artificial intelligence technique called genetic programming (GP) to make easier the programming of programmable logical devices (PLC) by the automatic generation of Ladder and Instruction List programs. The system data input can be done by not-specialized people using scenarios composed by time lines. These time lines demonstrate graphically the sequencing details of the PLC input and output permitting the programming of systems that uses memory like inter-locking contacts and the use of timers. Since GP is great dependent of its initial simulation parameters, thousand of simulations have been done to determine the better kind of configuration of cross-over and mutationItem Programação Genética Aplicada no Processo de Descoberta de Conhecimento em Bases de Dados de Redes de Pesquisa.(Universidade Federal de Goiás, 2010-12-20) DUARTE, Kedma Batista; BRITO, Leonardo da Cunha; http://lattes.cnpq.br/6660680440182900The Genetic Programming (GP) is a heuristic algorithm for Data Mining (DM), which can be applied to the classification task. This is a method of evolutionary computing inspired in the mechanisms of natural selection theory of Charles Darwin, declared in 1859 in his book "The Origin of Species." From an initial population, the method search over a number of generations to find solutions adapted to the environment of problem. The PG method was proposed in 1990 by John Koza, who demonstrated in one of its applications, the induction in formation of decision trees in the process of data classification. Within this context, the study developed in this work has as main objective the investigation of the concepts of PG and its application on a database of scientific collaboration networks, helping as a management tool in prospective studies of trends for the establishment of common axes in public policy of Science, Technology and Innovation (STI), focusing on regional development. The method is applied on a set of attributes, sorting them in order to identify similarity relationships between groups of researchers that comprise the network. The study involves the concepts of Knowledge Discovery in Databases (KDD) and Data Mining (DM). Networks of Scientific Collaboration, or Networks Research, are inserted in the context of small groups of social networks, the environment is dynamic due to the easy of information exchange and links between individuals, favoring the formation of new groups, which makes the growth of the network unlimited. "The combination of these groups, generated by the relationships between them, appears as a case of multi-criteria decision, granting the application of some complexity. In this sense, it is intended to apply the method of PG for generation of classification rules that lead to the discovery of groups of researchers with similar traits, which in a planned process could be induced to form groups strengthened and consolidated. The study helps to exploit the potential of genetic programming as a classifier algorithm, as well as use it as a method to build tools to support planning and decision making in STI.Item ROTEAMENTO AUTOMÁTICO DE ALIMENTADORES NO PLANEJAMENTO DE SISTEMAS DE DISTRIBUIÇÃO DE ENERGIA ELÉTRICA(Universidade Federal de Goiás, 2008-11-07) ROCHA, Adson Silva; BRITO, Leonardo da Cunha; http://lattes.cnpq.br/6660680440182900The present work deals with the problem of planning the distribution system of electricity and is divided into three parts: Problem Definition, Resolution Approaches and Results and Conclusions. The energy distribution networks are of great economic importance in countries like Brazil. On one hand, there are fixed costs of physical installation and operation of the network, mainly due to the costs of energy losses and, secondly, the natural obstacles along the possible passages of network s links. The large amount of these costs, together with lack of efficient methods when it comes to real applications in the matter, justify the development of this research. The study of such aspects, the precise definition of the problem and the reasons that motivated this work can be found on the first part of this work. The second part shows the approaches for resolution. Three proposals methods were adopted: the first uses the algorithm Prim associated with the method Nelder-Mead Simplex. In the second proposal uses Dynamic Programming and, finally, we take the metaphor of Ant Colony also associated with the Nelder-Mead Simplex. The results, presented at the third part of this work, demonstrated the effectiveness of the proposed methods, especially the good compromise between performance and applicability obtained by the third proposal.