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![Figure 2: General Procedures of Feature Selection. Source: [14]](https://thumb-ap.123doks.com/thumbv2/123dok/933988.904946/9.612.158.434.335.431/figure-general-procedures-feature-selection-source.webp)
![Figure 10: Performance’s dependence of network complexity. Source: [4], p.74](https://thumb-ap.123doks.com/thumbv2/123dok/933988.904946/16.612.191.407.97.288/figure-performance-s-dependence-network-complexity-source-p.webp)
![Figure 11: Performance’s dependence of the training mode. Source: [17], p.40.](https://thumb-ap.123doks.com/thumbv2/123dok/933988.904946/17.612.219.365.89.198/figure-performance-s-dependence-training-mode-source-p.webp)
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The Internet (including local area networks (LANS), wide area networks (WAN) and all electronic platforms for communication) is the primary means of data communications in
The interaction between group selection and grade point average is explained, and the paper concludes that the best group selection is to pair friends and then combine them to
Explores the different approaches used by several educational institu- tions in
Examines an increasingly important feature of further and higher education provi- sion: the development of distance-learning opportuni- ties for managers and teach- ers interested
Explains that the paradigm is cyclical having four phases each with several activities, and it was constructed by reviewing real-world practices in several interrelated
Abstract – The separation ahead of a forward facing step was investigated under laminar flow conditions using the hydrogen bubble technique to visualise and PTV to evaluate the
The objective of this study is to test, under relatively simple circumstances, whether flexible non-linear models — including neural networks and genetic algorithms — can
CONCLUSIONS This study investigated feed forward neural network FFNN and layered recurrent neural network LRNN models and a non-linear input selection technique using partial mutual
