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Improved Gravitation Field Algorithm and Its Application in Hierarchical Clustering

Overview of attention for article published in PLOS ONE, November 2012
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Title
Improved Gravitation Field Algorithm and Its Application in Hierarchical Clustering
Published in
PLOS ONE, November 2012
DOI 10.1371/journal.pone.0049039
Pubmed ID
Authors

Ming Zheng, Ying Sun, Gui-xia Liu, You Zhou, Chun-guang Zhou

Abstract

Gravitation field algorithm (GFA) is a new optimization algorithm which is based on an imitation of natural phenomena. GFA can do well both for searching global minimum and multi-minima in computational biology. But GFA needs to be improved for increasing efficiency, and modified for applying to some discrete data problems in system biology.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 10 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Luxembourg 1 10%
Unknown 9 90%

Demographic breakdown

Readers by professional status Count As %
Researcher 3 30%
Other 2 20%
Professor 1 10%
Lecturer > Senior Lecturer 1 10%
Student > Ph. D. Student 1 10%
Other 1 10%
Unknown 1 10%
Readers by discipline Count As %
Agricultural and Biological Sciences 3 30%
Computer Science 2 20%
Engineering 2 20%
Energy 1 10%
Decision Sciences 1 10%
Other 0 0%
Unknown 1 10%
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 17 November 2012.
All research outputs
#22,584,263
of 25,193,883 outputs
Outputs from PLOS ONE
#197,487
of 218,525 outputs
Outputs of similar age
#146,380
of 164,122 outputs
Outputs of similar age from PLOS ONE
#4,010
of 4,766 outputs
Altmetric has tracked 25,193,883 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 218,525 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.7. This one is in the 1st percentile – i.e., 1% 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 164,122 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 4,766 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.