Fingerprint The Elsevier Fingerprint Engine mines the text of the experts' scholarly documents – publication abstracts, awards, project summaries, patents, and other sources – to create an index of weighted terms which defines the text, known as a Fingerprint. By aggregating and comparing Fingerprints, the Elsevier Fingerprint Engine enables users to look beyond metadata and expose valuable connections among people, research units, publications, and ideas.

climate Earth & Environmental Sciences
aerosol Earth & Environmental Sciences
effect Earth & Environmental Sciences
simulation Earth & Environmental Sciences
climate change Earth & Environmental Sciences
particle Earth & Environmental Sciences
Aerosols Engineering & Materials Science
ozone Earth & Environmental Sciences

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Research Output 1973 2018

Machine learning to predict the global distribution of aerosol mixing state metrics

Hughes, M., Kodros, J. K., Pierce, J. R., West, M. & Riemer, N. Jan 9 2018 In : Atmosphere. 9, 1, 15

Research output: Research - peer-reviewArticle

climate modeling
machine learning
global climate
Statistical tests

Accommodating measurement uncertainty in the optimization of space flight trajectories

Zorn, A. & West, M. 2017 Spaceflight Mechanics 2017. Univelt Inc., Vol. 160, p. 811-822 12 p.

Research output: ResearchConference contribution

space flight
Space flight