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铸造工艺分析的神经网络方法_ppt.pdf
METRO
MEtallurgical TRaining On-line
Artificial neural networks in analysis
of foundry processes
Marcin Perzyk
WUT
Education and Culture
Definition of artificial neural
network (ANN)
Artificial neural network (ANN) is a complex mathematical
relationship, the structure of which imitates structure and data
processing in cerebral cortex of mammals, including humans.
Neuron (network knot)
Synapses transfer values of
variables and contain model
parameters – synapses weights.
Synapse
(connection of knots, Neurons perform mathematical
sometimes network output) operations on variables and
weights.
METRO – MEtallurgical TRaining On-line Copyright © 2005 Marcin Perzyk - WUT 2
Artificial neural networks
Basic advantages
• Ability to learn and to generalise the acquired
knowledge. ANNs are able to find regularities in
situations of large number of variables of various
types. Such regularities often cannot be detected by
senses of analysts or other mathematical models.
• ANN is resistant to noise in data as well as errors
appearing in some weights, i.e. incorrectly
determined individual model parameters.
• Fast data processing, sometimes online.
METRO – MEtallurgical TRaining On-line Copyright © 2005 Marcin Perzyk - WUT 3
Artificial neural networks
General characteristics
ANNs are learning systems type models. Values of model parameters
(network weights) are determined form results of observations (training
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