Trained ANN Parameters for Physics-inspired Artificial Neural Network for Dynamic Systemhttps://doi.org/10.18419/darus-634Praditia, TimothyDaRUS2020-07-212020-07-21T10:28:30ZThis 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.Computer and Information ScienceEarth and Environmental SciencesArtificial Neural NetworkPhysics-based RegularizationPhysics Inspired Neural NetworkThermochemical Energy StoragePraditia, T., Walser, T., Oladyshkin, S. and Nowak, W.: Improving Thermochemical Energy Storage dynamics forecast with Physics-Inspired Neural Network architecture. Energies 20202020-07-21Praditia, TimothyWalser, ThiloOladyshkin, SergeyNowak, Wolfgang2020-02-07Praditia, T. (2020): Input-Output Dataset for Physics-inspired Artificial Neural Network for Dynamic System, <a href="https://doi.org/10.18419/darus-633">doi: 10.18419/darus-633</a>, DaRUS.CC BY 4.0