The doi above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
doi: 10.4121/f1c54b90-a69c-4bd5-a55d-bfa9fa16fa40

Wang, Yi (2023): Data and code used in the article "A deep learning method for predicting soil moisture in unsaturated areas based on physical constraints". Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/f1c54b90-a69c-4bd5-a55d-bfa9fa16fa40.v1

Dataset

• Artificial Intelligence and Image Processing
• Land and Water Management
• Information and Computing Sciences
• Environment

deep learning, Hydrogeology, Long short-term memory networks (LSTM)

Restrictive Licence

RefWorks, BibTeX, Reference Manager, Endnote, DataCite, NLM, DC, CFF

by Yi Wang

Data and code used in the article "A deep learning method for predicting soil moisture in unsaturated areas based on physical constraints"，specifically included are water content data from 55 in situ observations for the years 2018-2020 (observation frequency of 5min or 10min), and example code for implementing LSTM and PCDL using python (mainly the tensorflow library).These data can help the reader to better understand and replicate our research

• 2023-05-15 first online, published, posted

4TU.ResearchData

code/.py; tables/.xlsx

Chang'an University