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Neural Computing and Applications

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01.09.2013 | New applications of Artificial Neural Networks in Modeling & Control

A survey of artificial neural network training tools

verfasst von: Darío Baptista, Fernando Morgado-Dias

Erschienen in: Neural Computing and Applications | Ausgabe 3-4/2013

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Abstract

Artificial neural networks (ANN) are currently an additional tool which the engineer can use for a variety of purposes. Classification and regression are the most common tasks; however, control, modeling, prediction and forecasting are common tasks as well. For over three decades, the field of ANN has been the center of intense research. As a result, one of the outcomes has been the development of a large set of software tools used to train these kinds of networks, making the selection of an adequate tool difficult for a new user. This paper aims to help the ANN user choose the most appropriate tool for its application by providing a large survey of the solutions available, as well as listing and explaining their characteristics and terms of use. The paper limits itself to focusing on the tools which were developed for ANN and the relevant characteristics of these tools, such as the operating systems, hardware requirements, license types, architectures and algorithms available.

Vorheriger Artikel Low-resource hardware implementation of the hyperbolic tangent for artificial neural networks

Nächster Artikel Fuzzy controllers gains tuning: a constrained nonlinear optimization approach

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Titel: A survey of artificial neural network training tools
verfasst von: Darío Baptista
Fernando Morgado-Dias
Publikationsdatum: 01.09.2013
Verlag: Springer London
Erschienen in: Neural Computing and Applications / Ausgabe 3-4/2013
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI: https://doi.org/10.1007/s00521-013-1408-9

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