1 to 10 of 15,301 Results
Jun 26, 2025
Raw and prepared datasets and trained models for the publication "Few-Shot Learning by Explicit Physics Integration: An Application to Groundwater Heat Transport", including randomized and real permeability fields, on different domain sizes (12.8kmx12.8km and double the size for scaling tests); DDUNet- and LGCNN architectures |
Zhang, Xiaoyu, 2024, "Models and Prepared Datasets for Iterative Modeling of Two Heat Pumps", https://doi.org/10.18419/DARUS-4518, DaRUS, V3
Prepared datasets and models for iterative modeling of heat plumes in groundwater. Models were trained with Iterative modeling. File explanation: 1HP.zip This zip file contains all prepared datapoints with a single heat pump. The input data fields are pressure, permeability, position of the heat pump, normalized distance to the heat pump, and tempe... |
ZIP Archive - 813.8 MB -
MD5: 3c5f8ee53e45f1a67870a2417bef7dd4
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ZIP Archive - 806.9 MB -
MD5: 0d329e714747cabd00c5028bec1c70c0
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ZIP Archive - 799.2 MB -
MD5: 2f56a18ad50b50024b95043d7531d484
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Dec 19, 2024
Hofmann, Johanna, 2024, "Models and Prepared Datasets for Convolutional Long Short-Term Memory (ConvLSTM) Networks", https://doi.org/10.18419/DARUS-4514, DaRUS, V2
The dataset contains trained ConvLSTM models for heat plume extension and the prepared dataset for training and testing. In this repo the code for model training and dataset preparation is published. The last relevant git commit is 0a148e6131b98260. The prepared dataset for training is called ep_medium_1000dp_only_vary_dist inputs_ks. It consists o... |
Dec 19, 2024 -
Models and Prepared Datasets for Convolutional Long Short-Term Memory (ConvLSTM) Networks
ZIP Archive - 683.6 MB -
MD5: 6d85ec6273279e3ed81b683f747ed5b6
This file contains the dataset prepared for the ConvLSTM for heat plume extension. |
Trick, Johanna, 2024, "Models and Prepared Datasets for 3D-CNN - First Stage", https://doi.org/10.18419/DARUS-4534, DaRUS, V1
Models trained with Heat Plume Prediction 3D and datasets prepared with Heat Plume Prediction 3D into reasonable format, normalization used to train these models. Based on raw data from doi:darus-4533. |
Nov 26, 2024 -
Models and Prepared Datasets for 3D-CNN - First Stage
Unknown - 164 B -
MD5: 04074ce881f8e0dd010c2b2c2c217078
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Nov 26, 2024 -
Models and Prepared Datasets for 3D-CNN - First Stage
Unknown - 165 B -
MD5: ace3532bd852f4d3cbbad822fb9e9889
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