Software baseado em rede neural artificial desenvolvido por meio de algoritmo genético para a classificação morfológica de blastocistos bovinos

Pós-graduação em Biociências - FCLAS

Um algoritmo de busca tabu para problemas de localização não capacitados

In this work, a tabu search algorithm for solving uncapacitated location problems is presented. The uncapacitated location problem is a classic problem of localization and occurs in many practical situations. The problem consists in determining in a network, at the minimum possible cost, the better localization, in a network, for the installation of facilities in order to attend the customers' associated demands, at the minimum possible cost. One admits that there exists a cost associated with the opening of a facility and a cost of attendance of each customer by any open facilities. In the particular case of the uncapacitated location problem there is no capacity limitation to attend the customers’ demands. There are some parameters in the algorithm that influence the solution’s quality. These parameters were tested and optimal values for them were obtained. The results show that the proposed algorithm is able to find the optimal solution for all small tested problems keeping the compromise between solution’s quality and computational time. However, to solve bigger problems, the structure of the algorithm must be changed in its structure. The implemented algorithm is integrated to a computational platform for solution of logistic problems

Paralelização de algoritmos de trimap utilizando a arquitetura Cuda

Techniques of image combination, with extraction of objects to set a final scene, are very used in applications from photos montages to cinematographic productions. These techniques are called digital matting. With them is possible to decrease the cost of productions, because it is not necessary for the actor to be filmed in the location where the final scene occurs. This feature also favors its use in programs made to digital television, which demands a high quality image. Many digital matting algorithms use markings done on the images, to demarcate what is the foreground, the background and the uncertainty areas. This marking is called trimap, which is a triple map containing these three informations. The trimap is done, typically, from manual markings. In this project, methods were created that can be used in digital matting algorithms, with restriction of time and without human interaction, that is, the creation of an algorithm that generates the trimap automatically. This last one can be generated from the difference between a color of an arbitrary background and the foreground, or by using a depth map. It was also created a matting method, based on the Geodesic Matting (BAI; SAPIRO, 2009), which has an inferior processing time then the original one. Aiming to improve the performance of the applications that generates the trimap and of the algorithms that generates the alphamap (map that associates a value to the transparency of each pixel of the image), allowing its use in applications with time restrictions, it was used the CUDA architecture. Taking advantage, this way, of the computational power and the features of the GPGPU, which is massively parallel

Desenvolvimento de solução para o problema de alocação de navios em berços de terminais portuários: aplicação de algoritmos genéticos e otimização por nuvens de partículas

This work proposes two optimization algorithms for the solution of the Berth Allocation Problem (PAB). Due to the economic development of the country, it became necessary for the improvement of means of transport, which mainly shipping. For this, you need a better system management port, you will receive a lot of ships carrying cargo. In this work the PAB is approached so that the goals are to reduce costs and time handling in ports. For this, we applied two computational techniques, genetic algorithms and optimization for cloud particles, to obtain the best results for this problem. The results obtained with each type of algorithm are compared to conclude which method is more efficient for the port system

Algoritmo de resolução de EDO de primeira ordem com implementação em HTML

This work presents a theoretical study of ordinary differential equations of first order directed so as to provide basis for the development of an educational software that helps students and researchers confronted with this issue. The algorithm was developed in HTML language in to that the results provide a website that allows the audience to access the software anywhere which has internet connection

Uso de algoritmos genéticos na otimização do sistema de coleta do palhiço de cana-de-açúcar

The Brazilian government has convinced the world that ethanol deriving from sugar cane is a promissory means of sustainable fuel for vehicles. There is a great growth of ex vehicles , i.e, run both by ethanol and gasoline, due to competent automotive industries and e cient alcohol production technology. In 2009 and 2010 the ethanol production was 25.7 billion liters and 53.8% of sugar cane production was destined to alcohol production. Nevertheless, the sugar production also derived from sugar cane should increase in 2011. Brazil produced 33 million tons of sugar in the last harvest. With sugar cane on the rise production is arising new environmental problems. The harvest using mechanized cut besides improving the logistic transportation system leaves the generating residue in the eld. This residue is a mixture of straw, leavings and scrap of sugar cane named sugar cane crop residue and corresponds to 30% of biomass and can be burned and produce electricity by cogeneration. But the transport the sugar cane crop from the eld is expensive due costs involved in the transport system. This work aims to propose a formulation for the bales collecting problem from sugar cane eld to mill that minimize the costs involved in the transport system. The computational tests use the C++ language and an algorithm based on genetic algorithms techniques

Uma proposta de resolução para problemas de roteirização de veículos baseada no algoritmo genético

The vehicle routing problem is to nd a better route to meet a set of customers who are geographically dispersed using vehicles that are a central repository to which they return after serving customers. These customers have a demand that must be met. Such problems have a wide practical application among them we can mention: school transport, distribution of newspapers, garbage collection, among others. Because it is a classic problem as NP-hard, these problems have aroused interest in the search for viable methods of resolution. In this paper we use the Genetic Algorithm as a resolution

Busca quântica de dados XML usando algoritmo de Grover

This paper presents a quantum search algorithm implementation with small modifications. The algorithm idea is to be hybrid, capable to run on classical systems and quantum systems. We present the concepts of quantum search and introduced a pseudo-framework able to generate code for classical computers (C++) and quantum computers (QCL). The algorithms were submitted to simulations, which resulted in a comparative study of the operation of Grover’s algorithm on both systems, carrying out searches in a mass of data in XML format files. As a result, we see very similar numbers between classical and quantum systems, this creates an expectation that the search in real quantum computers is much more efficient.

Algoritmo híbrido neural-imuno aplicado ao diagnóstico de distúrbios de tensão em sistemas de distribuição de energia elétrica

Pós-graduação em Engenharia Elétrica - FEIS

Algoritmo tabu search especializado para o problema de planejamento da expansao de sistemas de transmissão

Pós-graduação em Engenharia Elétrica - FEIS

Otimização da operação de sistemas de distribuição radiais usando um algoritmo genético especializado

Pós-graduação em Engenharia Elétrica - FEIS

Implementação do algoritmo de treinamento do classificador floresta de caminhos ótimos em GPU

Técnicas de reconhecimento de padrões tem como principal objetivo classificar um conjunto de amostras, sendo o processo de aprendizado a fase de maior consumo de tempo. O problema pode piorar em ferramentas de classificação interativas, o que pode ser inaceitável para grandes bases de dados. Um exemplo de classificador é o baseado em Floresta de Caminhos Ótimos [8] - OPF. Dado que muitos trabalhos tem sido orientados à implementação de algoritmos de reconhecimento de padrões em ambiente General Purpose Graphics Processing Unit - GPGPU, o presente estudo objetivou a implementação da etapa de treinamento do classificador Floresta de Caminhos Ótimos em CUDA, visando aumentar a sua eficiência. A otimização do classificador em CUDA demonstrou uma fase de treinamento mais rápida que a versão original.

Algoritmo da divisão de Euclides : uma nova proposta de ensino de matemática na educação básica

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Algoritmo neurogenético com vistas para o planejamento de rotas de robôs móveis autônomos

Pós-graduação em Ciência da Computação - IBILCE

Proposta de um algoritmo eficiente para a localização de faltas por relé diferencial numérico para proteção de linhas de transmissão com compensação série controlada por tiristores (TCSC)

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)