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A Bio-Inspired Self-Learning Coevolutionary Dynamic Multiobjective Optimization Algorithm for Internet of Things Services

Overview of attention for article published in IEEE Transactions on Evolutionary Computation, November 2018
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (60th percentile)
  • High Attention Score compared to outputs of the same age and source (93rd percentile)

Mentioned by

twitter
1 X user
patent
1 patent

Readers on

mendeley
58 Mendeley
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Article details
Title
A Bio-Inspired Self-Learning Coevolutionary Dynamic Multiobjective Optimization Algorithm for Internet of Things Services
Published in
IEEE Transactions on Evolutionary Computation, November 2018
DOI 10.1109/tevc.2018.2880458
Authors

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Timeline Attention over time Attention Score history
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Activity
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X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 58 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 58 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Master 12 21%
Student > Ph. D. Student 11 19%
Student > Doctoral Student 3 5%
Student > Postgraduate 3 5%
Lecturer 2 3%
Other 3 5%
Unknown 24 41%
Readers by discipline
Readers by discipline Count As %
Computer Science 15 26%
Engineering 5 9%
Social Sciences 2 3%
Mathematics 1 2%
Nursing and Health Professions 1 2%
Other 5 9%
Unknown 29 50%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 08 August 2025.
All research outputs
#9,773,347
of 29,321,408 outputs
Outputs from IEEE Transactions on Evolutionary Computation
#99
of 744 outputs
Outputs of similar age
#144,220
of 369,168 outputs
Outputs of similar age from IEEE Transactions on Evolutionary Computation
#2
of 29 outputs
Altmetric has tracked 29,321,408 research outputs across all sources so far. This one has received more attention than most of these and is in the 66th percentile.
So far Altmetric has tracked 744 research outputs from this source. They receive a mean Attention Score of 3.9. This one has done well, scoring higher than 85% 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 369,168 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 60% of its contemporaries.
We're also able to compare this research output to 29 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 93% of its contemporaries.