Minimization Artificial
Mostrando 1-12 de 12 artigos, teses e dissertações.
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1. Abordagens multi-objetivo para o treinamento de redes neurais e seleção de características
Artificial neural networks have been successfully applied in solving problems such as functions approximation and patterns classification, where the extraction of a model can be difficult to see. The search for a model that best represents the problem makes the generalization ability the main concern in the training of artificial neural networks, a task that
IBICT - Instituto Brasileiro de Informação em Ciência e Tecnologia. Publicado em: 02/03/2012
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2. Monitoramento por dgps e análise dos processos erosivos da linha de costa na praia de Pirangi do Norte - Parnamirim / RN
Through out the course of a steady increase in search and recovery of space in the coastal zone, there is also an expanding concern about the erosion processes of this area. The main problem in coastal areas is that urbanization occurs in a disorderly fashion and unsustainable, further aggravating the problems of coastal dynamics. The study area of this work
Publicado em: 2009
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3. Nuvem de partículas aplicada à seleção de atributos
Abstract: The particle swarm optimization (PSO) algorithm is a recently developed metaheuristic technique and belongs to the category of swarm intelligence techniques. The swarm intelligence concepts are inspired by the social behavior of flocking animals such as swarms of birds, ants and fish school. PSO is a population based algorithm that exploits a popul
Publicado em: 2008
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4. Propriedades de equilÃbrio e de transporte da matÃria de vÃrtices em nanoestruturas supercondutoras
In the present thesis, we study theoretically the equilibrium properties and dynamics of the vortex matter in two classes of nanostructured superconductors: (i) mesoscopic samples, with dimensions comparable with the penetration depth; and (ii) films with periodic array of artificial traps. In both cases, the vortex lattice symmetry is strongly dependent on
Publicado em: 2007
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5. Aspectos de mapas caóticos acoplados para processamento de informações / Aspects of chaotic coupled maps for information processing
A globally coupled map (GCM) model is a network of interconnected chaotic elements. In this work we investigate models based in the GCM and in the Hopfield network. Through modifications, like changing the local dynamics of the GCM (S-GCM) and adding self-feedback to the processing element of the Hopfield network, it s possible to use the models as an assoc�
Publicado em: 2002
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6. Algoritmos genéticos adaptativos: um estudo comparativo. / Genetic algorithm: a comparative study.
Os Algoritmos Genéticos representam, atualmente, uma poderosa ferramenta para busca de soluções de problemas com alto nível de complexidade. Esta dissertação estuda os Meta Algoritmos Genéticos, que é uma classe de Algoritmos Genéticos, e compara-os com os Algoritmos Genéticos tradicionais. Para a realização deste estudo, foi desenvolvido um prog
Publicado em: 2000
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7. Minimização de pedras em redes de distribuição de energia eletrica atraves de metodos de busca inteligentes com processamento paralelo
This thesis addresses the problem of loss minimization for electric energy distribution system. As distribution networks operates radially, the problem can be formulated as a generalization of minimum spanning tree problem. The minimum loss solution is obtained in two steps. The constraint of radial operation is relaxes in the first step, leading to an optim
Publicado em: 1999
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8. BAYESIAN LEARNING FOR NEURAL NETWORKS / APRENDIZADO BAYESIANO PARA REDES NEURAIS
This dissertation investigates the Bayesianan Neural Networks, which is a new approach that merges the potencial of the artificial neural networks with the robust analytical analysis of the Bayesian Statistic. Typically, theconventional neural networks such as backpropagation, have good performance but presents problems of convergence, when enough data for t
Publicado em: 1999
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9. Projeto e implementação em VLSI de uma rede neural auto-organizavel usando sintese automatica de auto nivel
: A Kohonen-based (SOFM - Self-Organizing Feature Map ) artificial neural network was simulated, modelated and hardware implemented in a VLSI circuit. A Top-Down methodological approach was used by using ANSI-C and VHDL (Very High Speed Circuits, Hardware Description Language). The original SOFM algorithm was lightly modified for customizing to the hardware
Publicado em: 1997
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10. Controle em destilação batelada : controle adaptativo e controle preditivo com modelo baseado em redes neurais artificiais
Separation processes are very important in chemical industries where batch distillation appears as one of its oldest processes. Over the last few years batch processing has received renewed attention because of the growing interest in the production of high-technology, high-value added chemical and biochemical products and also in environmental problems of i
Publicado em: 1995
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11. Formation of geometrically complex lipid nanotube-vesicle networks of higher-order topologies
We present a microelectrofusion method for construction of fluid-state lipid bilayer networks of high geometrical complexity up to fully connected networks with genus = 3 topology. Within networks, self-organizing branching nanotube architectures could be produced where intersections spontaneously arrange themselves into three-way junctions with an angle of
The National Academy of Sciences.
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12. Heteroduplexes in mixed-template amplifications: formation, consequence and elimination by ‘reconditioning PCR’
Although it has been recognized that PCR amplification of mixed templates may generate sequence artifacts, the mechanisms of their formation, frequency and potential elimination have not been fully elucidated. Here evidence is presented for heteroduplexes as a major source of artifacts in mixed-template PCR. Nearly equal proportions of homoduplexes and heter
Oxford University Press.