Physics informed neural networks for an inverse problem in peridynamic models
Deep learning is a powerful tool for solving data driven differential problems and has come
out to have successful applications in solving direct and inverse problems described by …
out to have successful applications in solving direct and inverse problems described by …
Inverse Physics-Informed Neural Networks for transport models in porous materials
Physics-Informed Neural Networks (PINN) are a machine learning tool that can be used to
solve direct and inverse problems related to models described by Partial Differential …
solve direct and inverse problems related to models described by Partial Differential …
Analysis of the Effect of Frequency on Wavelength and Sound Size in Sound Generator Experiments
RFM Firda, N Amelia, R Arisa, S Ullayla… - … Kalijaga Journal of … - ejournal.uin-suka.ac.id
Waves are one of the abstract physics materials in the world of physics and will be a
separate problem in studying them. The wave superposition experiment was carried out …
separate problem in studying them. The wave superposition experiment was carried out …