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Forecasting Damage Mechanics by Deep Learning
2019
Computers Materials & Continua
We in this paper exploit time series algorithm based deep learning in forecasting damage mechanics problems. The methodologies that are able to work accurately for less computational and resolving attempts are a significant demand nowadays. Relied on learning an amount of information from given data, the long short-term memory (LSTM) method and multi-layer neural networks (MNN) method are applied to predict solutions. Numerical examples are implemented for predicting fracture growth rates of
doi:10.32604/cmc.2019.08001
fatcat:x43kidqjp5bhrfngyrujwuwkxe