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Line search fixed point algorithms based on nonlinear conjugate gradient directions: application to constrained smooth convex optimization

Overview of attention for article published in Fixed Point Theory and Algorithms for Sciences and Engineering, July 2016
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About this Attention Score

  • Among the highest-scoring outputs from this source (#23 of 185)

Mentioned by

twitter
1 X user

Citations

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3 Dimensions

Readers on

mendeley
4 Mendeley
Title
Line search fixed point algorithms based on nonlinear conjugate gradient directions: application to constrained smooth convex optimization
Published in
Fixed Point Theory and Algorithms for Sciences and Engineering, July 2016
DOI 10.1186/s13663-016-0567-7
Authors

Hideaki Iiduka

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

Geographical breakdown

Country Count As %
Unknown 4 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 1 25%
Researcher 1 25%
Student > Master 1 25%
Unknown 1 25%
Readers by discipline Count As %
Mathematics 2 50%
Sports and Recreations 1 25%
Unknown 1 25%
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 09 July 2016.
All research outputs
#17,285,668
of 25,373,627 outputs
Outputs from Fixed Point Theory and Algorithms for Sciences and Engineering
#23
of 185 outputs
Outputs of similar age
#240,924
of 370,765 outputs
Outputs of similar age from Fixed Point Theory and Algorithms for Sciences and Engineering
#1
of 2 outputs
Altmetric has tracked 25,373,627 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 185 research outputs from this source. They receive a mean Attention Score of 0.7. This one has done well, scoring higher than 81% 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 370,765 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 2 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them