A survey of artificial neural network training tools

TitleA survey of artificial neural network training tools
Publication TypeJournal Article
Year of Publication2013
AuthorsBaptista, D., and D. F. Morgado
JournalNeural Computing and Applications [Impact Factor SJR2012: 1.168]
Volume23
Pagination609-615
Date Published2013
ISSN0941-0643
KeywordsArtificial Neural Networks, Software, Training algorithms, Training tools
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.

URLhttp://dx.doi.org/10.1007/s00521-013-1408-9
DOI10.1007/s00521-013-1408-9