NeuroFramework: A package based on neuroevolutionary algorithms to estimate the melting temperature of ionic liquids

In this paper, a Neuroevolutionary framework is presented for training and testing neuroevolutionary algorithms. This algorithm offers flexibility in its design by the stacking of operators to form an algorithm prototype. This approach allows a faster algorithm design where operators can be stacked...

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Main Authors: Jorge Alberto Cerecedo-Cordoba, Juan Frausto-Solís, Juan Javier González Barbosa
Format: Article
Language:English
Published: Elsevier 2020-01-01
Series:SoftwareX
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2352711019302924
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author Jorge Alberto Cerecedo-Cordoba
Juan Frausto-Solís
Juan Javier González Barbosa
author_facet Jorge Alberto Cerecedo-Cordoba
Juan Frausto-Solís
Juan Javier González Barbosa
author_sort Jorge Alberto Cerecedo-Cordoba
collection DOAJ
description In this paper, a Neuroevolutionary framework is presented for training and testing neuroevolutionary algorithms. This algorithm offers flexibility in its design by the stacking of operators to form an algorithm prototype. This approach allows a faster algorithm design where operators can be stacked in the training phase and can even be managed by a dynamic controller. Neural Networks are represented on a graph without layers. This software was designed in modularity and new features can be easily added. This software includes a wrapper for Python for machine learning tasks, especially regression; however, the user can adapt this package for classification.
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spelling doaj.art-745e2e17a1534e9382500b3d9a2cb2e02022-12-21T17:17:25ZengElsevierSoftwareX2352-71102020-01-0111NeuroFramework: A package based on neuroevolutionary algorithms to estimate the melting temperature of ionic liquidsJorge Alberto Cerecedo-Cordoba0Juan Frausto-Solís1Juan Javier González Barbosa2Tecnológico Nacional de México/Instituto Tecnológico de Ciudad Madero, Avenida Primero de Mayo, 89440, Cuidad Madero, Tamaulipas, MexicoCorresponding author.; Tecnológico Nacional de México/Instituto Tecnológico de Ciudad Madero, Avenida Primero de Mayo, 89440, Cuidad Madero, Tamaulipas, MexicoTecnológico Nacional de México/Instituto Tecnológico de Ciudad Madero, Avenida Primero de Mayo, 89440, Cuidad Madero, Tamaulipas, MexicoIn this paper, a Neuroevolutionary framework is presented for training and testing neuroevolutionary algorithms. This algorithm offers flexibility in its design by the stacking of operators to form an algorithm prototype. This approach allows a faster algorithm design where operators can be stacked in the training phase and can even be managed by a dynamic controller. Neural Networks are represented on a graph without layers. This software was designed in modularity and new features can be easily added. This software includes a wrapper for Python for machine learning tasks, especially regression; however, the user can adapt this package for classification.http://www.sciencedirect.com/science/article/pii/S2352711019302924Neuroevolutionary algorithmsIonic liquidsNeural networks
spellingShingle Jorge Alberto Cerecedo-Cordoba
Juan Frausto-Solís
Juan Javier González Barbosa
NeuroFramework: A package based on neuroevolutionary algorithms to estimate the melting temperature of ionic liquids
SoftwareX
Neuroevolutionary algorithms
Ionic liquids
Neural networks
title NeuroFramework: A package based on neuroevolutionary algorithms to estimate the melting temperature of ionic liquids
title_full NeuroFramework: A package based on neuroevolutionary algorithms to estimate the melting temperature of ionic liquids
title_fullStr NeuroFramework: A package based on neuroevolutionary algorithms to estimate the melting temperature of ionic liquids
title_full_unstemmed NeuroFramework: A package based on neuroevolutionary algorithms to estimate the melting temperature of ionic liquids
title_short NeuroFramework: A package based on neuroevolutionary algorithms to estimate the melting temperature of ionic liquids
title_sort neuroframework a package based on neuroevolutionary algorithms to estimate the melting temperature of ionic liquids
topic Neuroevolutionary algorithms
Ionic liquids
Neural networks
url http://www.sciencedirect.com/science/article/pii/S2352711019302924
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