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An asynchronous recurrent linear threshold network approach to solving the traveling salesman problem

Overview of attention for article published in Neurocomputing, March 2008
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1 X user

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8 Mendeley
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Title
An asynchronous recurrent linear threshold network approach to solving the traveling salesman problem
Published in
Neurocomputing, March 2008
DOI 10.1016/j.neucom.2007.06.006
Authors

E.J. Teoh, K.C. Tan, H.J. Tang, C. Xiang, C.K. Goh

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

Geographical breakdown

Country Count As %
Unknown 8 100%

Demographic breakdown

Readers by professional status Count As %
Student > Postgraduate 3 38%
Lecturer > Senior Lecturer 1 13%
Student > Doctoral Student 1 13%
Lecturer 1 13%
Professor 1 13%
Other 1 13%
Readers by discipline Count As %
Computer Science 3 38%
Engineering 3 38%
Design 1 13%
Unknown 1 13%
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 12 October 2015.
All research outputs
#20,657,128
of 25,374,917 outputs
Outputs from Neurocomputing
#1,971
of 2,954 outputs
Outputs of similar age
#88,577
of 95,559 outputs
Outputs of similar age from Neurocomputing
#5
of 6 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,954 research outputs from this source. They receive a mean Attention Score of 2.7. This one is in the 26th percentile – i.e., 26% 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 95,559 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 3rd percentile – i.e., 3% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 6 others from the same source and published within six weeks on either side of this one.