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The effect of internal parameters and geometry on the performance of back-propagation neural networks: an empirical study

โœ Scribed by Holger R. Maier; Graeme C. Dandy


Publisher
Elsevier Science
Year
1998
Tongue
English
Weight
501 KB
Volume
13
Category
Article
ISSN
1364-8152

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In recent years, back-propagation neural networks have become a popular tool for modelling environmental systems. However, as a result of the relative newness of the technique to this field, users appear to have limited knowledge about how ANNs operate and how to optimise their performance. In this