Neural Network for Predicting Soil Thermal Conductivity

Published: 25 October 2024| Version 1 | DOI: 10.17632/by2xmg7jvc.1
Contributor:
Yongwei Fu

Description

The uploaded files are the referenced dataset for the article "Neural network prediction of thermal conductivity across full saturation for various soil types" submitted to Agricultural Forest and Meteorology. It comprises two folders: 1. “Model Prediction” Folder: This folder contains the complete dataset utilized in this study, along with the trained neural network (py and pth files). It enables users to reproduce the results presented in Figure 8 (training and testing outcomes) and facilitates the application of the model to additional soil datasets. 2. “Global Map of Model Parameters” Folder: This folder demonstrates an example application of the trained model, where the authors used SSCBD data from a global hydraulic properties dataset to generate and visualize the global distribution of the MLD model parameters.

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Categories

Machine Learning, Soil Physics, Neural Network, Soil Water Content

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