A Framework for Developing the Next Generation Interactive Soil Moisture Forecasting System Using the Long-Short Term Memory Model-Reference-Cited by-同舟云学术

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A Framework for Developing the Next Generation Interactive Soil Moisture Forecasting System Using the Long-Short Term Memory Model

Published:2023-12-15 Issue: Volume:14 Page:1986-1993
ISSN:
Container-title:2023 International Conference on Machine Learning and Applications (ICMLA)
language:
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Author:

M Guna Shekar¹,Lee Wonjun²,Kumar Sanjiv³,Duan Yanan³,Rangwala Imtiaz⁴

Affiliation:

1. California State University,Department of Computer Science,California

2. Biola University,Department of Math and Computer Science,La Mirada,CA

3. College of Forestry, Wildlife, and Environment Auburn University,Auburn

4. University of Colorado,NC CASC and CIRES,Boulder

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10459339/10459727/10459841.pdf?arnumber=10459841

Reference19 articles.

1. Research on soil moisture prediction model based on deep learning

2. Merging and Downscaling Soil Moisture Data From CMIP6 Projections Using Deep Learning Method

3. Improving soil moisture prediction using a novel encoder-decoder model with residual learning;Li,2022

4. Soil Moisture Prediction from Remote Sensing Images Coupled with Climate, Soil Texture and Topography via Deep Learning;Celik,2022

5. The Community Earth System Model Version 2 (CESM2)

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