Normalization methods for input and output vectors in backpropagation neural networks

DOI10.1080/00207169908804800zbMath0930.68136OpenAlexW2044606692MaRDI QIDQ4243251

Daehyon Kim

Publication date: 17 May 1999

Published in: International Journal of Computer Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00207169908804800

zbMATH Keywords

neural networksbackpropagation

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05)

Related Items (3)

U-Net-Based Surrogate Model for Evaluation of Microfluidic Channels ⋮ Prediction performance of support vector machines on input vector normalization methods ⋮ Improved training of physics-informed neural networks for parabolic differential equations with sharply perturbed initial conditions

Cites Work

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