Revisiting Atmospheric Features of Mars Orbiter Laser Altimeter Data Using Machine Learning Algorithms-Reference-Cited by-同舟云学术

Revisiting Atmospheric Features of Mars Orbiter Laser Altimeter Data Using Machine Learning Algorithms

Published:2023-01 Issue:1 Volume:128 Page:
ISSN:2169-9097
Container-title:Journal of Geophysical Research: Planets
language:en
Short-container-title:JGR Planets

Author:

Caillé Vincent¹^ORCID,Määttänen Anni¹^ORCID,Spiga Aymeric²^ORCID,Falletti Lola¹^ORCID

Affiliation:

1. LATMOS/IPSL Sorbonne Université UVSQ Paris‐Saclay CNRS Paris France

2. Laboratoire de Météorologie Dynamique/Institut Pierre Simon Laplace (LMD/IPSL) Sorbonne Université, Centre National de la Recherche Scientifique (CNRS), École Polytechnique, École Normale Supérieure (ENS) Paris France

Funder

Agence Nationale de la Recherche

Publisher

American Geophysical Union (AGU)

Subject

Space and Planetary Science,Earth and Planetary Sciences (miscellaneous),Geochemistry and Petrology,Geophysics

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1029/2022JE007384

Reference62 articles.

1. Mars Orbiter Laser Altimeter: receiver model and performance analysis

2. NONHIERARCHICAL CLUSTERING METHODS

3. Mariner 9 Television Limb Observations of Dust and Ice Hazes on Mars

4. Arthur D. &Vassilvitskii S.(2006).How slow is thek‐means method?InProceedings of the twenty‐second annual symposium on Computational geometry ‐ SCG (Vol.6 pp.144–153).https://doi.org/10.1145/1137856.1137880

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