Synonyms
Definition
An artificial neural network (ANN), usually called neural network (NN), is a mathematical model or computational model that is inspired by the structure and/or functional aspects of biological neural networks. A neural network consists of an interconnected group of artificial neurons, and it processes information using a connectionist approach to computation. In most cases, an ANN is an adaptive system that changes its structure based on external or internal information that flows through the network during the learning phase. Modern neural networks are nonlinear statistical data modeling tools. They are usually used to model complex relationships between inputs and outputs or to find patterns in data.
Extended Definition
The term neural network was traditionally used to refer to a network or circuit of biological neurons (Hopfield 1982). Modern usage of the term often refers to artificial neural networks, which are...
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Balabin RM, Lomakina EI (2009) Neural network approach to quantum-chemistry data: accurate prediction of density functional theory energies. J Chem Phys 131(7):074104
Hopfield JJ (1982) Neural networks and physical systems with emergent collective computational abilities. Proc NatL Acad Sci USA 79:2554–2558, April 1982 Biophysics
Siegelmann HT, Sontag ED (1991) Turing computability with neural nets. Appl Math Lett 4(6):77–80
The Machine Learning Dictionary. http://www.cse.unsw.edu.au/∼billw/mldict.html#activnfn
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 CIRP
About this entry
Cite this entry
D’Addona, D.M. (2014). Neural Network. In: Laperrière, L., Reinhart, G. (eds) CIRP Encyclopedia of Production Engineering. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20617-7_6563
Download citation
DOI: https://doi.org/10.1007/978-3-642-20617-7_6563
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-20616-0
Online ISBN: 978-3-642-20617-7
eBook Packages: EngineeringReference Module Computer Science and Engineering