...
should be divided into several sets (training, testing, production, on-line, remaining). The
training set is used to adjust the interconnection weights of the MPNN model. The testing
set is used ... local minimum far from the global one. During the learning process,
the network should be periodically tested on the testing set (not included in the training set)
www.intechopen.com
Artificial ... feedforward networks. Neural
Networks 4, pp. 251-257
Kohonen, T. (1995). Self-organizing maps. Springer, Berlin
Kurkova, V. (1992). Kolmogorov’s Theorem and Multilayer Neural Networks, Neural
Networks, ...
... pilling, finger marks, and others.
free online editions of InTech
Books and Journals can be found at
www.intechopen.com
ArtificialNeuralNetworks - Industrial and Control Engineering Applications
Edited ... application of ANN in textiles and clothing
industries will be addressed in last section.
ArtificialNeuralNetworks - Industrial and Control Engineering Applications
6
neural net produced ... 2011
Printed in India
A free online edition of this book is available at www.intechopen.com
Additional hard copies can be obtained from orders@intechweb.org
Artificial NeuralNetworks - Industrial...
... 14.14GPa which is
corresponding to the sintering temperature of 1420°C and the holding time of 80min, while
ArtificialNeuralNetworks - Industrial and Control Engineering Applications
158
2.5 ... algorithm in the optimization
of hot pressing parameters
ArtificialNeuralNetworks - Industrial and Control Engineering Applications
162
The depicting effect of mentioned factors and their interactions ... the input layer to the hidden layer as the transfer function and
ArtificialNeuralNetworks - Industrial and Control Engineering Applications
134
input and output vector values are in the...
... for use in
training and testing the neural network. A large training data reduces
the risk of under-sampling the nonlinear function, but increases the
training time. To improve training, preprocessing ...
minmax
min
VV
VV
A
−
−
=
(4)
Training was performed iteratively until the average of sum squared
error over all the training patterns was minimized. Experiment were
carried out using ...
DESIGN ARTIFICIALNEURAL NETWORK MODEL
Neural networks are computer models that mimic the knowledge
acquisition and organization skills of the human brain. Since, the
characteristics of a neural...
... of NeuralNetworks 163
Hazem M. El-Bakry
Chapter 9 Applying ArtificialNeural Network Hadron - Hadron
Collisions at LHC 183
Amr Radi and Samy K. Hindawi
Chapter 10 Applications of ArtificialNeural ... as a method to realize flexible infor‐
mation processing. Neuralnetworks consider neuron groups of the brain in the creature,
and imitate these neurons technologically. Neuralnetworks have some ... Pattern Recognition by Self-organizing Neu‐
ral Networks. The MIT Press.
Artificial NeuralNetworks – Architectures and Applications2 2
16 Artificial Neural Networks
Figure 11. The expectation...
... ArtificialNeuralNetworks - Industrial and Control Engineering Applications
42
organizing feature map neural network. There were ten input neurons corresponding to ten
feature indexes and ... 1000 spindle hours; by means of inputs including the
processing parameters such as fiber properties, spinning method, and process variables
influencing on the yarn properties and spinning performance. ... representing five cluster centers (five pilling grades)
by training twenty kinds of samples including colored and patterned pilled worsted fabrics.
The total number of iterations in the training...
... percentage
ArtificialNeuralNetworks - Industrial and Control Engineering Applications
88
Sao, K.P. & Jain, A. K. (1995). Mercerization and crimp formation in jute. Indian Journal ... of Intelligent Methods for Evaluating the
Apparent Quality of Knitted Fabrics. Engineering Applications of Artificial Intelligence,
Vol.23, pp. 217-221, ISSN 0952-1976
ArtificialNeuralNetworks ... by linear
connection with linear or nonlinear transformations. The weights were determined by
training the neural nets. Once the ANN was trained, it was used for predicting new sets of
inputs....
... trainin
g
2
nd
ANN trainin
g
3
rd
ANN trainin
g
4
th
ANN trainin
g
5
th
ANN trainin
g
Randoml
y
initialized wei
g
hts & biases
Wei
g
hts & biases from the 1
st
trainin
g
1
st
trainin
g
... for inputs too far beyond.
2.1 Neural network training algorithms
Artificial neuralnetworks are used as an interdisciplinary tool in many types of nonlinear
problems. In order to design a neural ... step training; (b) – in the beginning of the 2
nd
step training; (c) – at the end of the training. On each screenshot: the menu on the left
defines training parameters; the graph in middle-top...
... Precipitation in North Carolina. Water, Air, and Soil Pollution, 172,
167.
ArtificialNeuralNetworks - Industrial and Control Engineering Applications
176
for testing. For the training stage, ... (as-received)
ArtificialNeuralNetworks - Industrial and Control Engineering Applications
168
Botlani-Esfahani. M, Toroghinejad. M. R. and Abbasi. Sh. (2009b) ArtificialNeural Network
Modeling the ... structures in a coal mine using
Artificial Neural Networks.
International Journal of Rock Mechanics and Mining
Sciences, Volume 45, Issue 6, 999-1006.
Wasserman, P.D. (1993).
Advanced methods in neural...
... 150-158(9)
Part 3
Food Industry
ArtificialNeuralNetworks - Industrial and Control Engineering Applications
232
ANN was investigated, is given in Table 2. In regard to carcass classification ...
propagation error. Learning of the network was carried out using 9 data points from the
ArtificialNeuralNetworks - Industrial and Control Engineering Applications
228
networks is given by ... near-infrared spectroscopy: Linear and nonlinear calibration methods
Journal of the American Oil Chemists' Society, 83(5)
ArtificialNeuralNetworks - Industrial and Control Engineering Applications...