Enhancing agricultural automation through weather invariant soil parameter prediction using machine learning-Reference-Cited by-同舟云学术

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Enhancing agricultural automation through weather invariant soil parameter prediction using machine learning

Published:2024-04 Issue:7 Volume:10 Page:e28626
ISSN:2405-8440
Container-title:Heliyon
language:en
Short-container-title:Heliyon

Author:

Uttsha Monisha Mushtary,Haque A.K.M. Nadimul,Banna Tahsin Tariq,Deowan Shamim Ahmed,Ariful Islam Md.,Hasan Babu Hafiz Md.

Funder

Government of the People's Republic of Bangladesh Ministry of Science and Technology

Publisher

Elsevier BV

Reference49 articles.

1. Bayesian estimation of spatially varying soil parameters with spatiotemporal monitoring data;Yang;Acta Geotech.,2021

2. Monitoring soil and ambient parameters in the iot precision agriculture scenario: an original modeling approach dedicated to low-cost soil water content sensors;Placidi;Sensors,2021

3. Monitoring of soil parameters for effective irrigation using wireless sensor networks;Bhanu,2014

4. Soil quality—the key to a sustainable agriculture;Papendick;Am. J. Altern. Agric.,1992

5. Environmental impact of greenhouse tomato production in France;Boulard;Agron. Sustain. Dev.,2011

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1. Development and evaluation of interpretable machine learning regressors for predicting femoral neck bone mineral density in elderly men using NHANES data;Biomolecules and Biomedicine;2024-07-05

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