Extraction Of Knowledge From Artificial Neural Networks
Mostrando 1-6 de 6 artigos, teses e dissertações.
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1. O uso de redes neurais auto-organizÃveis na anÃlise da transferÃncia de conhecimentos prosÃdico em aprendizes brasileirios de lÃngua inglesa / The use of self-organizing artificial neural networks for the analysis of prosodic knowledge in Brazilian learner of English
The objective of this dissertation was to investigate how the prosodic knowledge is organized in an early stage of L2 acquisition in Brazilian learners of English with the help of a connectionist neural network. The approach proposed in this research is first, to quantify the utterances of L2 learners in the form of LPC coefficients and other linguistic/phon
IBICT - Instituto Brasileiro de Informação em Ciência e Tecnologia. Publicado em: 08/10/2010
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2. Extração de conhecimento a partir de redes reurais recorrentes / knowledge extraction from recurrent neural networks
ln this work a method ofknowledge extraction from Recurrent Neural Network is proposed. Express formally the knowledge stored inside an Artificial Neural Network is a great challenge, because such knowledge has to be reformulated and presented by simple and understandable means. Three symbolic formats are presented for the representation of this knowledge: F
Publicado em: 2004
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3. Desenvolvimento de uma plataforma hÃbrida para descoberta de conhecimento em bases de dados
Artificial Neural Networks (ANN) have successfully been used in tasks as the mapping of complex functions and pattern recognition. This success is due to the ANN ability to make calculations of complicated and undetermined data, learn from examples, generalize the learned information, extract patterns and discover tendencies. Despite these advantages, it is
Publicado em: 2004
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4. HIBRID NEURO-FUZZY-GENETIC SYSTEM FOR AUTOMATIC DATA MINING / SISTEMA HÍBRIDO NEURO-FUZZY-GENÉTICO PARA MINERAÇÃO AUTOMÁTICA DE DADOS
This dissertation presents the proposal and the development of a totally automatic data mining system. The main objective is to create a system that is capable of extracting obscure information from complex databases, without demanding the presence of a technical specialist to configure it. The Hierarchical Neuro-Fuzzy Binary Space Partitioning model (NFHB)
Publicado em: 2004
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5. Extraction of knowledge from Artificial Neural Networks using Symbolic Machine Learning Systems and Genetic Algorithm / "Extração de conhecimento de redes neurais artificiais utilizando sistemas de aprendizado simbólico e algoritmos genéticos"
In Machine Learning - ML there is not a single algorithm that is the best for all application domains. In practice, several research works have shown that Artificial Neural Networks - ANNs have an appropriate inductive bias for several domains. Thus, ANNs have been applied to a number of data sets with high predictive accuracy. Symbolic ML algorithms have a
Publicado em: 2003
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6. Extração de conhecimento de redes neurais artificiais. / Knowledge extraction from artificial neural networks.
This work describes experiments carried out witch Artificial Neural Networks and symbolic learning algorithms. Two algorithms for knowledge extraction from Artificial Neural Networks are also investigates. This experiments are performed whit three data set with the objective of compare the performance obtained. The data set used in this work are: Brazilians
Publicado em: 1999