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Global optimization test problems based on random field composition

Overview of attention for article published in Optimization Letters, May 2016
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2 X users

Citations

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Readers on

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12 Mendeley
Title
Global optimization test problems based on random field composition
Published in
Optimization Letters, May 2016
DOI 10.1007/s11590-016-1037-1
Authors

Ramses Sala, Niccolò Baldanzini, Marco Pierini

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 12 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Russia 1 8%
Unknown 11 92%

Demographic breakdown

Readers by professional status Count As %
Researcher 3 25%
Professor 2 17%
Unspecified 1 8%
Student > Bachelor 1 8%
Student > Ph. D. Student 1 8%
Other 1 8%
Unknown 3 25%
Readers by discipline Count As %
Engineering 5 42%
Unspecified 1 8%
Physics and Astronomy 1 8%
Computer Science 1 8%
Unknown 4 33%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 16 July 2018.
All research outputs
#19,519,579
of 24,002,307 outputs
Outputs from Optimization Letters
#181
of 506 outputs
Outputs of similar age
#223,916
of 302,345 outputs
Outputs of similar age from Optimization Letters
#5
of 5 outputs
Altmetric has tracked 24,002,307 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
So far Altmetric has tracked 506 research outputs from this source. They receive a mean Attention Score of 0.8. This one has gotten more attention than average, scoring higher than 55% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 302,345 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 13th percentile – i.e., 13% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 5 others from the same source and published within six weeks on either side of this one.