An Early Stopping-Based Artificial Neural Network Model for Atmospheric Corrosion Prediction of Carbon Steel

The optimization of network topologies to retain the generalization ability by deciding when to stop overtraining an artificial neural network (ANN) is an existing vital challenge in ANN prediction works. The larger the dataset the ANN is trained with, the better generalization the prediction can gi...

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Vydané v:	Computers, materials & continua Ročník 65; číslo 3; s. 2091 - 2109
Hlavní autori:	Hnin Thike, Phyu, Zhao, Zhaoyang, Liu, Peng, Bao, Feihu, Jin, Ying, Shi, Peng
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Henderson Tech Science Press 2020
Predmet:	Algorithms Artificial neural networks Atmospheric corrosion Atmospheric models Back propagation networks Carbon steel Carbon steels Correlation coefficients Datasets Multilayers Network topologies Neural networks Prediction models Topology optimization
ISSN:	1546-2226, 1546-2218, 1546-2226
On-line prístup:	Získať plný text
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