Machine learning for predicting greenhouse gas emissions from agricultural soils-Reference-Cited by-同舟云学术

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Machine learning for predicting greenhouse gas emissions from agricultural soils

Published:2020-11 Issue: Volume:741 Page:140338
ISSN:0048-9697
Container-title:Science of The Total Environment
language:en
Short-container-title:Science of The Total Environment

Author:

Hamrani Abderrachid,Akbarzadeh Abdolhamid,Madramootoo Chandra A.

Funder

Agriculture and Agri-Food Canada

Publisher

Elsevier BV

Subject

Pollution,Waste Management and Disposal,Environmental Chemistry,Environmental Engineering

Reference102 articles.

1. Dynamic neural network modelling of soil moisture content for predictive irrigation scheduling;Adeyemi;Sensors,2018

2. Effects of agriculture upon the air quality and climate: research, policy, and regulations;Aneja;Environ. Sci. Technol.,2009

3. Modern corn hybrids’ nutrient uptake patterns. Better crop. With plant food;Bender;Int. Plant Nutr. Inst.,2013

4. Gradient-based optimization of hyperparameters;Bengio;Neural Comput.,2000

5. A lysimeter study on the effect of temperature on CO2 emission from cultivated peat soils;Berglund;Geoderma,2010

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