... include two wide
luminescence bands at around 460 nm (blue band) and 515 nm (green band). These bands are
characterized by the vacancies of Zn bonding to Cl (V
Zn
-Cl) and some impurities in ZnS ... green band decrease. Hence, at x
Cu
= 5.10
-4
mol% the intensities of these two
bands are equal to each other and they merge into one wide band ranging from 476 nm to 533 nm. The
blue and green ... in ZnS and Co in ZnO, the self-activated luminescence bands characterized
by vacancies of zinc and oxygen are extinguished or their intensities decrease. In PL spectra of
ZnS:Cu, ZnS:Mn and ZnO:Co...
... Example
Orthogonal Input Vectors Example
Variations andApplications of Kohonen Networks
C++ NeuralNetworksand Fuzzy Logic:Preface
Preface 8
C++ NeuralNetworksand Fuzzy Logic
by Valluru B. Rao
MTBooks, ... Anyone?
Stability and Plasticity
Stability for a Neural Network
Plasticity for a Neural Network
Short−Term Memory and Long−Term Memory
Summary
Chapter 5—A Survey of Neural Network Models
C++ NeuralNetworksand ... Fuzzy Sets
Applications of Fuzzy Logic
Examples of Fuzzy Logic
Commercial Applications
Fuzziness in Neural Networks
Code for the Fuzzifier
Fuzzy Control Systems
Fuzziness in NeuralNetworks
Neural Trained...
... For Such diverse and cutting-edge technology conventional systems
have proved expendable and arduous. It is when the ArtificialNeuralNetworksand Fuzzy
Systems have proved their speed competitive ... monitored and controlled simultaneously,
and it is quite difficult to derive classical structured models, on account of practical
ArtificialNeuralNetworks - Industrial and Control Engineering Applications ... composition and quality analysis
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226
objects from different classes or having different properties). Clusters and empty...
... 312-355, ISSN: 0891-2513
Cartwright, H. M. (2008). Artificialneuralnetworks in biology and chemistry. In: Artificial
neural networks : methods and applications. Livingstone, D. (Ed.), 1-13, Humana ...
Table 4. Other applications of ANN in meat science and technology
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260
smoothen the response and cancel high-frequency ... Table 3.
Fig. 8. Actual structure of neural network.
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246
abandon various kinds of irrational points that...
... Figures 7 to 8 and the target patterns for generator located at buses 14 and 22 are given in
Figures 9 to 12.
ArtificialNeuralNetworks - Industrial and Control Engineering Applications
...
of 186 lines, 33 physical reactive power sources and 54 real power generators.
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270
Input vectors in the upper ... reactive power transfer between generators and loads with almost similar
accuracy.
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286
where
'
Y is the...
... automata on lattices and random graphs, motivated by the structural
Biologically Plausible ArtificialNeural Networks
http://dx.doi.org/10.5772/54177
37
8 Artificial Neural Networks
Figure 7. The ... supercritical Andronov-Hopf bifurcation,
the equilibrium state loses stability and gives rise to a small amplitude limit cycle attractor.
Artificial NeuralNetworks – Architectures and Applications3 2
... correct patterns even when
the noisy input was given.
Artificial NeuralNetworks – Architectures and Applications1 6
2 Artificial Neural Networks
1.1. McCulloch-Pitts neuron
McCulloch-Pitts neuron...
... of the
ARTIFICIALNEURAL
NETWORKS ͳ
INDUSTRIAL AND CONTROL
ENGINEERING
APPLICATIONS
Edited by Kenji Suzuki
Review of Application of ArtificialNeuralNetworks
in Textiles and Clothing ...
spinning ends-
down and neps
ArtificialNeuralNetworks - Industrial and Control Engineering Applications
4
2. Applications to fibres and yarns
2.1 Fibre classification
Kang and Kim (2002) ... different
ArtificialNeuralNetworks - Industrial and Control Engineering Applications
12
3.5 Seam performance
Hui and Ng (2009) investigated the capability of artificialneural networks...
... as artificialneural network
(ANN model) by alkali concentration, temperature and time as inputs. Both statistical model
ArtificialNeuralNetworks - Industrial and Control Engineering Applications ... of
data are available
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44
Semnani & Vadood, 2009 applied the artificialneural network (ANN) to predict ... feature index, and finally assessing pilling grade by Kohonen self
ArtificialNeuralNetworks - Industrial and Control Engineering Applications
42
organizing feature map neural network....
... 2009a and Debnath & Roy, 1999) and percentage
ArtificialNeuralNetworks - Industrial and Control Engineering Applications
88
Sao, K.P. & Jain, A. K. (1995). Mercerization and ... layers; and SD – Standard deviation
Table 15. Experimental and predicted values of initial thickness by ANN model
ArtificialNeuralNetworks - Industrial and Control Engineering Applications ... layers; and SD – Standard deviation
Table 16. Experimental and predicted values of percentage compression by ANN model
ArtificialNeuralNetworks - Industrial and Control Engineering Applications...
... same elemental
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102
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
andesite AGV2
andesite JA1
andesite JA2
andesite JA3
anorthosite ... acceptable.
ArtificialNeuralNetworks - Industrial and Control Engineering Applications
98
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
andesite AGV2
andesite JA1
andesite JA2
andesite JA3
anorthosite ... the networksandtheir accuracies, the
Fig. 5. Regression analysis of K' for the train and test data and (σ
y
, S
u
, RA% and BHN) as
ANN input.
ArtificialNeuralNetworks for...
... the transfer function andArtificialNeuralNetworks - Industrial and Control Engineering Applications
134
input and output vector values are in the real number space and there are no effects ... prepared and the mechanical properties
were tested.
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156
Fig. 3. Schematic architecture of ArtificialNeural ... of 85vol%ZrO
2
, 8vol%TiB
2
and 7vol%Al
2
O
3
is the better.
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150
5.4 Results and discussion
According to...
... ArtificialNeuralNetworks - Industrial and Control Engineering Applications
182
Karacan, C.O. (2007). Development and application of reservoir models andartificialneural
networks ... inference system
In the artificial intelligence field, the term “neuro-fuzzy” refers to combinations of artificial
neural networksand fuzzy logic. Fuzzy modeling andneuralnetworks have been recognized ... dynamic model
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192
Once the artificialneural network is trained, which means that all of the weights and bias
are...
...
the random frequency and amplitude changes of SOI and FRP.
Fig. 10. Random signal of SOI for training and validation
Fig. 11. Random signal of FRP for training and validation
The Applications ... application of artificialneuralnetworks on engine applications.
Several practical examples show the applicability of artificialneuralnetworks in the domain
of virtual sensing and control development ... (1-8) mm and 16 mm with their corresponding hardness
85-175 and 175-275 respectively, for the types of cutting tools listed in Table 2.
ArtificialNeuralNetworks - Industrial and Control...