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A visual toolbox for modeling and testing multi‐net neural systems
Author(s) -
Melin Patricia,
Mendoza Olivia,
Castillo Oscar,
Castro Juan Ramon
Publication year - 2013
Publication title -
computer applications in engineering education
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.478
H-Index - 29
eISSN - 1099-0542
pISSN - 1061-3773
DOI - 10.1002/cae.20459
Subject(s) - toolbox , computer science , modular design , artificial neural network , set (abstract data type) , artificial intelligence , machine learning , software engineering , programming language
Neural networks (NN) and muti‐net neural systems are popular and important topics for graduate engineering students. This paper describes a visual toolbox that has been developed to perform experiments with new multi‐net neural structures, including ensemble and modular NN approaches. This toolbox can be considered an important contribution for graduate engineering education and research because it is a complete tool that allows to draw models, set parameters, save projects, and generate files with results in a user friendly visual environment. Experimental results with a group of students after using the toolbox show a significant improvement on the acquired knowledge of NNs concepts. © 2010 Wiley Periodicals, Inc. Comput Appl Eng Educ 21: 164–184, 2013