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Applying nature-inspired optimization algorithms for selecting important timestamps to reduce time series dimensionality

Overview of attention for article published in Evolving Systems, November 2017
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Mentioned by

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1 X user

Citations

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2 Dimensions

Readers on

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15 Mendeley
Title
Applying nature-inspired optimization algorithms for selecting important timestamps to reduce time series dimensionality
Published in
Evolving Systems, November 2017
DOI 10.1007/s12530-017-9207-7
Authors

Muhammad Marwan Muhammad Fuad

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

Geographical breakdown

Country Count As %
Unknown 15 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 4 27%
Researcher 3 20%
Student > Ph. D. Student 1 7%
Other 1 7%
Student > Doctoral Student 1 7%
Other 1 7%
Unknown 4 27%
Readers by discipline Count As %
Computer Science 4 27%
Engineering 2 13%
Mathematics 1 7%
Decision Sciences 1 7%
Biochemistry, Genetics and Molecular Biology 1 7%
Other 0 0%
Unknown 6 40%
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 11 December 2018.
All research outputs
#20,545,598
of 23,117,738 outputs
Outputs from Evolving Systems
#26
of 29 outputs
Outputs of similar age
#287,157
of 329,495 outputs
Outputs of similar age from Evolving Systems
#2
of 2 outputs
Altmetric has tracked 23,117,738 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 29 research outputs from this source. They receive a mean Attention Score of 2.0. This one scored the same or higher as 3 of them.
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 329,495 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 2 others from the same source and published within six weeks on either side of this one.