Models and Prepared Datasets for Iterative Modeling of Two Heat Pumps

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 temperature. 2HP.zip This zip file contains all prepared datapoints with two heat pumps. The input data fields are pressure, permeability, position of the heat pump, normalized distance to the heat pump, and temperature. 3HP_raw.zip This zip file contains all raw datapoints with three heat pumps. 5HP_raw.zip This zip file contains all raw datapoints with five heat pumps. unet_stand_f64_d5_k4_2500dp This folder contains the model for the standard architecture. F stands for the number of initial features, d for the depth of the network, and k for the kernel size. The amount of datapoints the model was trained on is indicated by dp. unet_para_f64_d5_k4_pcs_2500dp This folder contains the model for the parallel architecture. F stands for the number of initial features, d for the depth of the network, and k for the kernel size. The amount of datapoints the model was trained on is indicated by dp. unet_quad_f64_d5_k4_2500dp This folder contains the model for the quadratic architecture. F stands for the number of initial features, d for the depth of the network, and k for the kernel size. The amount of datapoints the model was trained on is indicated by dp.

精心准备的数据集与模型，旨在迭代模拟地下水热羽流。模型采用迭代建模方法进行训练。文件说明：1HP.zip 该压缩文件包含单个热泵的所有准备好的数据点。输入数据字段包括压力、渗透率、热泵位置、热泵归一化距离和温度。2HP.zip 该压缩文件包含两个热泵的所有准备好的数据点。输入数据字段包括压力、渗透率、热泵位置、热泵归一化距离和温度。3HP_raw.zip 该压缩文件包含三个热泵的所有原始数据点。5HP_raw.zip 该压缩文件包含五个热泵的所有原始数据点。unet_stand_f64_d5_k4_2500dp 该文件夹包含标准架构的模型。F代表初始特征的数目，d代表网络的深度，k代表内核大小。模型训练所使用的数据点数量由dp指示。unet_para_f64_d5_k4_pcs_2500dp 该文件夹包含并行架构的模型。F代表初始特征的数目，d代表网络的深度，k代表内核大小。模型训练所使用的数据点数量由dp指示。unet_quad_f64_d5_k4_2500dp 该文件夹包含二次架构的模型。F代表初始特征的数目，d代表网络的深度，k代表内核大小。模型训练所使用的数据点数量由dp指示。