Multilayer Perceptrons
Mostrando 13-17 de 17 artigos, teses e dissertações.
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13. Um estudo comparativo de tÃcnicas conexionistas na implementaÃÃo de um sistena de reconhecimento de padrÃes para um nariz artificial
O principal objetivo desta dissertaÃÃo à fazer um estudo sistemÃtico sobre os diversos tipos de redes neurais artificiais (e seus respectivos algoritmos de aprendizagem) que vÃm sendo utilizados na implementaÃÃo do sistema de reconhecimento de padrÃes do nariz artificial proposto em [Santos, 2000], apontando suas vantagens e desvantagens. Os modelos
Publicado em: 2003
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14. Redes neurais e suas aplicações em calibração multivariada
Neural Networks are a set of mathematical methods and computer programs designed to simulate the information process and the knowledge acquisition of the human brain. In last years its application in chemistry is increasing significantly, due the special characteristics for model complex systems. The basic principles of two types of neural networks, the mult
Química Nova. Publicado em: 2001-12
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15. Analise e previsões de vasões utilizando modelos de series temporais, redes neurais e redes neurais nebulosas
Analysis and forecast of seasonal stream flow series are of utmost importance in the operation planning of water resources systems. One of the greatest difficulties in forecasting of those series is the seasonality nature of stream flow series due to wet and dry periods of the year. For a long time, the use of stochastic models, based on the c1assic Box &Jen
Publicado em: 2000
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16. Fault detection and diagnosis in robotic manipulators via artificial neural networks. / Detecção e diagnóstico de falhas em robôs manipuladores via redes neurais artificiais.
In this work, a new approach for fault detection and diagnosis in robotic manipulators is presented. A faulty robot could cause serious damages and put in risk the people involved. Usually, researchers have proposed fault detection and diagnosis schemes based on the mathematical model of the system. However, modeling errors could obscure the fault effects an
Publicado em: 1999
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17. Systematic Learning of Gene Functional Classes From DNA Array Expression Data by Using Multilayer Perceptrons
Recent advances in microarray technology have opened new ways for functional annotation of previously uncharacterised genes on a genomic scale. This has been demonstrated by unsupervised clustering of co-expressed genes and, more importantly, by supervised learning algorithms. Using prior knowledge, these algorithms can assign functional annotations based on
Cold Spring Harbor Laboratory Press.