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A functional network to predict fresh and hardened properties of self‐compacting concretes
Author(s) -
Tomasiello Stefania
Publication year - 2011
Publication title -
international journal for numerical methods in biomedical engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.741
H-Index - 63
eISSN - 2040-7947
pISSN - 2040-7939
DOI - 10.1002/cnm.1333
Subject(s) - generalization , convergence (economics) , simple (philosophy) , set (abstract data type) , artificial neural network , scheme (mathematics) , computer science , algorithm , artificial intelligence , mathematics , mathematical analysis , philosophy , epistemology , economics , programming language , economic growth
Literature offers several examples of application of neural networks to predict fresh and hardened properties of conventional and self‐compacting concretes. In this paper, these issues are addressed to a relatively recent computational scheme given by the functional networks, by proposing an initial simple application. The algorithm with some appropriate assumptions, reveals a quick convergence and an interesting generalization capability even if the training data set is poor. Copyright © 2009 John Wiley & Sons, Ltd.