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Theory and Practice of Natural Computing

Overview of attention for book
Attention for Chapter 7: MOEA/D with Adaptative Number of Weight Vectors
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1 X user

Readers on

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3 Mendeley
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Chapter title
MOEA/D with Adaptative Number of Weight Vectors
Chapter number 7
Book title
Lecture Notes in Computer Science
Published in
Lecture notes in computer science, November 2021
DOI 10.1007/978-3-030-90425-8_7
Book ISBNs
978-3-03-090424-1, 978-3-03-090425-8
Authors

Lavinas, Yuri, Teru, Abe Mitsu, Kobayashi, Yuta, Aranha, Claus

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 readers

Mendeley readers

The data shown below were compiled from readership statistics for 3 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 3 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 1 33%
Student > Bachelor 1 33%
Unknown 1 33%
Readers by discipline Count As %
Engineering 2 67%
Computer Science 1 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 08 November 2021.
All research outputs
#16,821,472
of 24,736,359 outputs
Outputs from Lecture notes in computer science
#4,722
of 8,157 outputs
Outputs of similar age
#258,058
of 434,065 outputs
Outputs of similar age from Lecture notes in computer science
#16
of 24 outputs
Altmetric has tracked 24,736,359 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 8,157 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.2. This one is in the 27th percentile – i.e., 27% 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 434,065 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 29th percentile – i.e., 29% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 24 others from the same source and published within six weeks on either side of this one. This one is in the 12th percentile – i.e., 12% of its contemporaries scored the same or lower than it.