Applicability of Machine Learning Model to Simulate Atmospheric CO₂ Variability-Reference-Cited by-同舟云学术

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Applicability of Machine Learning Model to Simulate Atmospheric CO₂ Variability

Published:2022 Issue: Volume:60 Page:1-6
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

Girach Imran A.¹,Ponmalar M.²,Murugan S.³,Rahman P. Abdul⁴,Babu S. Suresh¹^ORCID,Ramachandran Radhika¹^ORCID

Affiliation:

1. Space Physics Laboratory, Vikram Sarabhai Space Centre, Thiruvananthapuram, ISRO, India

2. ISRO Inertial Systems Unit, Thiruvananthapuram, ISRO, India

3. ISRO Propulsion Complex, Mahendragiri, ISRO, India

4. Satish Dhawan Space Centre, Sriharikota, ISRO, India

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Earth and Planetary Sciences,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/36/9633014/09729865.pdf?arnumber=9729865

Reference16 articles.

1. Analysis of trends in fused AVHRR and MODIS NDVI data for 1982–2006: Indication for a CO 2 fertilization effect in global vegetation

2. Comparisons of the Orbiting Carbon Observatory-2 (OCO-2) <i>X</i><sub>CO<sub>2</sub></sub> measurements with TCCON

4. The Use of Cumulative Monthly Mean Temperature Anomalies in the Analysis of Local Interannual Climate Variability

5. On Splitting Training and Validation Set: A Comparative Study of Cross-Validation, Bootstrap and Systematic Sampling for Estimating the Generalization Performance of Supervised Learning

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