This dataverse contains dataset and codes for the submitted publication: Praditia, T., Walser, T., Oladyshkin, S. and Nowak, W. (2020): Physics-inspired Artificial Neural Network structure improves prediction: Application to a Thermochemical Energy Storage System
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MS Excel Spreadsheet - 19.1 KB - MD5: 9b88868eeef277937d0c729615e217de
ANN parameters for the regularization method "MSE+L2+PHY"
MS Excel Spreadsheet - 18.7 KB - MD5: 9a85fe1d359cb162a8c4bc183545ce46
ANN parameters for the regularization method "MSE+L2"
MS Excel Spreadsheet - 19.0 KB - MD5: 1b13a37e8fb1bf8ee2630519982ae0e4
ANN parameters for the regularization method "MSE+PHY"
MS Excel Spreadsheet - 18.5 KB - MD5: ed241c309250b1d17eb682b750fa1244
ANN parameters for the regularization method "MSE"
Markdown Text - 3.0 KB - MD5: 3aa442599a974dcf6b70ad2c45da506c
README file explaining how the data is formatted
MATLAB Data - 493.4 MB - MD5: 4368b82d61d591e5e7b76228741d13ae
This .mat file contains unprocessed input-output data pairs needed to train, validate, and test the ANN.
MATLAB Data - 93.0 MB - MD5: 5969cb06f84d4ed2348759c6091666eb
This .mat file contains processed input-output data pairs needed to train, validate, and test the ANN.
Markdown Text - 5.8 KB - MD5: 8feed08cd30f2e759181799d8ed814e1
README file explaining how the data is formatted
Shell Script - 5.2 MB - MD5: 92f8320c9a0e19c57b61ba939e14a1df
An automated script to run all samples in DuMuX for reproduction of the input-output data contained in the 'io_data.mat' and 'noisy_data.mat'. Before running, the path to the DuMuX executables needs to be adjusted accordingly.
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