Sirena : um simulador de redes neurais artificiais

AUTOR(ES)
DATA DE PUBLICAÇÃO

1994

RESUMO

Artificial Neural Net (ANN) is a model that emulates a Biological Neural Net. The ANN field has showed very promising which can be verified by the number of published papers and scientific events. In spite, to reach the desired ANN applications scope, many of ANN current limitations have to be overcome since it is not yet and well established the ANN functioning . There is no good and complete methodologies for construct ANN applications, i.e., for a specific problem to be solved, no methodology indicates what the net topology is, the learning algorithm and the sample of information suitable to the desired performance. If there is no methodology that indicates the better combination of the ANN elements to a specific application, the users have the option to start from a theoretical base and, by using empirical methods, begin constructing personal rules that indicates. the better combination of neural elements. The execution of this technique is difficulty because the number of variables that need to be evaluated during the net development process The focus of this work is facilitate the understanding of the ANN functioning through the user familiarization with its elements. A ANN simulator named Sirena was developed and its graphical interface aim to minimize the understanding difficulties of the low level processes executed by ANNs. During the simulation process one can access to several qualitative and quantitative representations that reflect the net alterations in the learning and inference phases

ASSUNTO(S)

redes neurais (computação) simulação (computadores digitais)

ACESSO AO ARTIGO

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