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Matching island topologies to problem structure in parallel evolutionary algorithms

Overview of attention for article published in Soft Computing, March 2013
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2 X users

Citations

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19 Mendeley
Title
Matching island topologies to problem structure in parallel evolutionary algorithms
Published in
Soft Computing, March 2013
DOI 10.1007/s00500-013-0995-9
Authors

Ignacio Arnaldo, Iván Contreras, David Millán-Ruiz, J. Ignacio Hidalgo, Natalio Krasnogor

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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 19 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Japan 1 5%
Unknown 18 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 4 21%
Researcher 3 16%
Student > Postgraduate 2 11%
Professor > Associate Professor 2 11%
Student > Doctoral Student 1 5%
Other 4 21%
Unknown 3 16%
Readers by discipline Count As %
Computer Science 7 37%
Engineering 4 21%
Agricultural and Biological Sciences 1 5%
Physics and Astronomy 1 5%
Mathematics 1 5%
Other 0 0%
Unknown 5 26%
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 22 October 2018.
All research outputs
#17,465,866
of 25,621,213 outputs
Outputs from Soft Computing
#306
of 557 outputs
Outputs of similar age
#134,842
of 208,433 outputs
Outputs of similar age from Soft Computing
#5
of 6 outputs
Altmetric has tracked 25,621,213 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 557 research outputs from this source. They receive a mean Attention Score of 3.5. This one is in the 25th percentile – i.e., 25% of its peers scored the same or lower than it.
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 208,433 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 26th percentile – i.e., 26% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 6 others from the same source and published within six weeks on either side of this one.