|
[1]
|
Development of a model for estimation of soil parameters using deep learning
International Journal of Information Technology,
2024
DOI:10.1007/s41870-023-01675-z
|
|
|
|
|
[2]
|
Enhancing Subsurface Soil Moisture Forecasting: A Long Short-Term Memory Network Model Using Weather Data
Agriculture,
2024
DOI:10.3390/agriculture14030333
|
|
|
|
|
[3]
|
A multihead LSTM technique for prognostic prediction of soil moisture
Geoderma,
2023
DOI:10.1016/j.geoderma.2023.116452
|
|
|
|
|
[4]
|
Estimate soil moisture of maize by combining support vector machine and chaotic whale optimization algorithm
Agricultural Water Management,
2022
DOI:10.1016/j.agwat.2022.107618
|
|
|
|
|
[5]
|
Deep Learning for Sustainable Agriculture
2022
DOI:10.1016/B978-0-323-85214-2.00001-X
|
|
|
|
|
[6]
|
Multistep Forecasting of Soil Moisture Using Spatiotemporal Deep Encoder–Decoder Networks
Journal of Hydrometeorology,
2022
DOI:10.1175/JHM-D-21-0131.1
|
|
|
|
|
[7]
|
Estimate soil moisture of maize by combining support vector machine and chaotic whale optimization algorithm
Agricultural Water Management,
2022
DOI:10.1016/j.agwat.2022.107618
|
|
|
|
|
[8]
|
A Spatial Downscaling Method for Remote Sensing Soil Moisture Based on Random Forest Considering Soil Moisture Memory and Mass Conservation
Remote Sensing,
2022
DOI:10.3390/rs14163858
|
|
|
|
|
[9]
|
Integration of machine learning and particle filter approaches for forecasting soil moisture
Stochastic Environmental Research and Risk Assessment,
2022
DOI:10.1007/s00477-022-02258-3
|
|
|
|
|
[10]
|
Estimate soil moisture of maize by combining support vector machine and chaotic whale optimization algorithm
Agricultural Water Management,
2022
DOI:10.1016/j.agwat.2022.107618
|
|
|
|
|
[11]
|
Soil Moisture Prediction of Maize by Combining Support Vector Machine and Chaotic Whale Optimization Algorithm
SSRN Electronic Journal ,
2022
DOI:10.2139/ssrn.4008734
|
|
|
|
|
[12]
|
Point-of-use sensors and machine learning enable low-cost determination of soil nitrogen
Nature Food,
2021
DOI:10.1038/s43016-021-00416-4
|
|
|
|
|
[13]
|
Point-of-use sensors and machine learning enable low-cost determination of soil nitrogen
Nature Food,
2021
DOI:10.1038/s43016-021-00416-4
|
|
|
|
|
[14]
|
Advances in soil moisture retrieval from multispectral remote sensing using unoccupied aircraft systems and machine learning techniques
Hydrology and Earth System Sciences,
2021
DOI:10.5194/hess-25-2739-2021
|
|
|
|
|
[15]
|
LSTM integrated with Boruta-random forest optimiser for soil moisture estimation under RCP4.5 and RCP8.5 global warming scenarios
Stochastic Environmental Research and Risk Assessment,
2021
DOI:10.1007/s00477-021-01969-3
|
|
|
|
|
[16]
|
Examination of Susceptibility to the Deficiency of Soil Water in a Forested Agricultural Area
Earth,
2021
DOI:10.3390/earth2030031
|
|
|
|
|
[17]
|
Machine Learning for Predicting Field Soil Moisture Using Soil, Crop, and Nearby Weather Station Data in the Red River Valley of the North
Soil Systems,
2021
DOI:10.3390/soilsystems5040057
|
|
|
|
|
[18]
|
Weekly soil moisture forecasting with multivariate sequential, ensemble empirical mode decomposition and Boruta-random forest hybridizer algorithm approach
CATENA,
2019
DOI:10.1016/j.catena.2019.02.012
|
|
|
|
|
[19]
|
Assessment of remotely sensed soil moisture products and their quality improvement: A case study in South Korea
Journal of Hydro-environment Research,
2019
DOI:10.1016/j.jher.2019.04.002
|
|
|
|
|
[20]
|
Using data‐driven methods to explore the predictability of surface soil moisture with FLUXNET site data
Hydrological Processes,
2019
DOI:10.1002/hyp.13540
|
|
|
|
|
[21]
|
Using data‐driven methods to explore the predictability of surface soil moisture with FLUXNET site data
Hydrological Processes,
2019
DOI:10.1002/hyp.13540
|
|
|
|
|
[22]
|
Soil Moisture Prediction Using Machine Learning
2018 Second International Conference on Inventive Communication and Computational Technologies (ICICCT),
2018
DOI:10.1109/ICICCT.2018.8473260
|
|
|
|
|
[23]
|
Use of Multivariate Relevance Vector Machines in forecasting multiple geomagnetic indices
Journal of Atmospheric and Solar-Terrestrial Physics,
2017
DOI:10.1016/j.jastp.2016.11.002
|
|
|
|
|
[24]
|
A Data-Driven Approach to Soil Moisture Collection and Prediction
2016 IEEE International Conference on Smart Computing (SMARTCOMP),
2016
DOI:10.1109/SMARTCOMP.2016.7501673
|
|
|
|
|
[25]
|
Estimation of Surface Soil Moisture in Irrigated Lands by Assimilation of Landsat Vegetation Indices, Surface Energy Balance Products, and Relevance Vector Machines
Water,
2016
DOI:10.3390/w8040167
|
|
|
|