PINN Dynamic System

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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1 to 10 of 11 Results

Trained ANN Parameters for Physics-inspired Artificial Neural Network for Dynamic System Jul 21, 2020 Praditia, Timothy, 2020, "Trained ANN Parameters for Physics-inspired Artificial Neural Network for Dynamic System", https://doi.org/10.18419/darus-634, DaRUS, V1 This dataset contains four .xlsx files containing trained values of the ANN weights and biases, along with the hyperparameter values at the end of the training (with noisy dataset). These four files correspond to four different regularization methods.
ANN_params_MSE_L2_PHY.xlsx Jul 21, 2020 - Trained ANN Parameters for Physics-inspired Artificial Neural Network for Dynamic System MS Excel Spreadsheet - 19.1 KB - MD5: 9b88868eeef277937d0c729615e217de ANN parameters for the regularization method "MSE+L2+PHY"
ANN_params_MSE_L2.xlsx Jul 21, 2020 - Trained ANN Parameters for Physics-inspired Artificial Neural Network for Dynamic System MS Excel Spreadsheet - 18.7 KB - MD5: 9a85fe1d359cb162a8c4bc183545ce46 ANN parameters for the regularization method "MSE+L2"
ANN_params_MSE_PHY.xlsx Jul 21, 2020 - Trained ANN Parameters for Physics-inspired Artificial Neural Network for Dynamic System MS Excel Spreadsheet - 19.0 KB - MD5: 1b13a37e8fb1bf8ee2630519982ae0e4 ANN parameters for the regularization method "MSE+PHY"
ANN_params_MSE.xlsx Jul 21, 2020 - Trained ANN Parameters for Physics-inspired Artificial Neural Network for Dynamic System MS Excel Spreadsheet - 18.5 KB - MD5: ed241c309250b1d17eb682b750fa1244 ANN parameters for the regularization method "MSE"
README.md Jul 21, 2020 - Trained ANN Parameters for Physics-inspired Artificial Neural Network for Dynamic System Markdown Text - 3.0 KB - MD5: 3aa442599a974dcf6b70ad2c45da506c README file explaining how the data is formatted
Input-Output Dataset for Physics-inspired Artificial Neural Network for Dynamic System Jul 21, 2020 Praditia, Timothy, 2020, "Input-Output Dataset for Physics-inspired Artificial Neural Network for Dynamic System", https://doi.org/10.18419/darus-633, DaRUS, V1 This dataset contains two .mat files, one pre-processed (direct simulation results) and the other one is with added noise. The simulated problem is a thermochemical energy storage problem using CaO/Ca(OH)2 as the material choice. This dataset is used as input-output data pairs ne...
io_data.mat Jul 21, 2020 - Input-Output Dataset for Physics-inspired Artificial Neural Network for Dynamic System MATLAB Data - 493.4 MB - MD5: 4368b82d61d591e5e7b76228741d13ae This .mat file contains unprocessed input-output data pairs needed to train, validate, and test the ANN.
noisy_data.mat Jul 21, 2020 - Input-Output Dataset for Physics-inspired Artificial Neural Network for Dynamic System MATLAB Data - 93.0 MB - MD5: 5969cb06f84d4ed2348759c6091666eb This .mat file contains processed input-output data pairs needed to train, validate, and test the ANN.
README.md Jul 21, 2020 - Input-Output Dataset for Physics-inspired Artificial Neural Network for Dynamic System Markdown Text - 5.8 KB - MD5: 8feed08cd30f2e759181799d8ed814e1 README file explaining how the data is formatted

Trained ANN Parameters for Physics-inspired Artificial Neural Network for Dynamic System

Jul 21, 2020

Praditia, Timothy, 2020, "Trained ANN Parameters for Physics-inspired Artificial Neural Network for Dynamic System", https://doi.org/10.18419/darus-634, DaRUS, V1

This dataset contains four .xlsx files containing trained values of the ANN weights and biases, along with the hyperparameter values at the end of the training (with noisy dataset). These four files correspond to four different regularization methods.

ANN_params_MSE_L2_PHY.xlsx

Jul 21, 2020 - Trained ANN Parameters for Physics-inspired Artificial Neural Network for Dynamic System

MS Excel Spreadsheet - 19.1 KB -

ANN parameters for the regularization method "MSE+L2+PHY"

ANN_params_MSE_L2.xlsx

Jul 21, 2020 - Trained ANN Parameters for Physics-inspired Artificial Neural Network for Dynamic System

MS Excel Spreadsheet - 18.7 KB -

ANN parameters for the regularization method "MSE+L2"

ANN_params_MSE_PHY.xlsx

Jul 21, 2020 - Trained ANN Parameters for Physics-inspired Artificial Neural Network for Dynamic System

MS Excel Spreadsheet - 19.0 KB -

ANN parameters for the regularization method "MSE+PHY"

ANN_params_MSE.xlsx

Jul 21, 2020 - Trained ANN Parameters for Physics-inspired Artificial Neural Network for Dynamic System

MS Excel Spreadsheet - 18.5 KB -

ANN parameters for the regularization method "MSE"

README.md

Jul 21, 2020 - Trained ANN Parameters for Physics-inspired Artificial Neural Network for Dynamic System

Markdown Text - 3.0 KB -

README file explaining how the data is formatted

Input-Output Dataset for Physics-inspired Artificial Neural Network for Dynamic System

Jul 21, 2020

Praditia, Timothy, 2020, "Input-Output Dataset for Physics-inspired Artificial Neural Network for Dynamic System", https://doi.org/10.18419/darus-633, DaRUS, V1

This dataset contains two .mat files, one pre-processed (direct simulation results) and the other one is with added noise. The simulated problem is a thermochemical energy storage problem using CaO/Ca(OH)2 as the material choice. This dataset is used as input-output data pairs ne...

io_data.mat

Jul 21, 2020 - Input-Output Dataset for Physics-inspired Artificial Neural Network for Dynamic System

MATLAB Data - 493.4 MB -

This .mat file contains unprocessed input-output data pairs needed to train, validate, and test the ANN.

noisy_data.mat

Jul 21, 2020 - Input-Output Dataset for Physics-inspired Artificial Neural Network for Dynamic System

MATLAB Data - 93.0 MB -

This .mat file contains processed input-output data pairs needed to train, validate, and test the ANN.

README.md

Jul 21, 2020 - Input-Output Dataset for Physics-inspired Artificial Neural Network for Dynamic System

Markdown Text - 5.8 KB -

README file explaining how the data is formatted

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