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vol.72 issue147MOLECULAR WEIGHT DISTRIBUTION ESTIMATION IN BATCH POLYESTERIFICATION USING A MODEL-BASED SOFT SENSORCONSUMER PRICE INDEX MODELLING USING AN ARTIFICIAL NEURAL NETWORKS-BASED HYBRID MODEL author indexsubject indexarticles search
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DYNA

Print version ISSN 0012-7353On-line version ISSN 2346-2183

Abstract

VELASQUEZ HENAO, JUAN DAVID. NEUROSCHEME: A MODELING LANGUAGE FOR ARTIFICIAL NEURAL NETWORKS. Dyna rev.fac.nac.minas [online]. 2005, vol.72, n.147, pp.75-83. ISSN 0012-7353.

Building of neural network-based models, is conformed not only by the creation of the artificial neural network and its training, but other number of activities realized before and after of this phase too. In the market exists many computational tools for artificial time series modelling, however, they are not enough versatile for doing these additional task. For satisfying this necessity, the Neuroscheme algorithmic language is developed, which incorporate the artificial neural networks models as a native type of data inside the language; it is characterized by its expression capacity, elegance and simplicity.

Keywords : artificial neural networks; programming languages; declarative languages.

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