Rbf Radial Basis Functions Networks
Mostrando 1-2 de 2 artigos, teses e dissertações.
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1. Neural networks forecasting and classification-based techniques for novelty detection in time series
Novelty detection can be defined as the identification of new or unknown data that a machine learning system is not aware during training. Novelty detection algorithms are designed to classify input patterns as normal or novelty. These algorithms are used in several areas such as computer vision, machine fault detection, network security and fraud detection.
Publicado em: 2004
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2. Model Selection of RBF Networks Via Genetic Algorithms
One of the main obstacles to the widespread use of artificial neural networks is the difficulty of adequately defining values for their free parameters. This work discusses how Radial Basis Function (RBF) neural networks can have their free parameters defined by Genetic Algorithms (GAs). For such, it firstly presents an overall view of the problems involved
Publicado em: 2003