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Massively Parallel Computation Using Graphics Processors with Application to Optimal Experimentation in Dynamic Control

Overview of attention for article published in Computational Economics, October 2011
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1 Google+ user

Citations

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19 Dimensions

Readers on

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27 Mendeley
Title
Massively Parallel Computation Using Graphics Processors with Application to Optimal Experimentation in Dynamic Control
Published in
Computational Economics, October 2011
DOI 10.1007/s10614-011-9297-4
Authors

Sergei Morozov, Sudhanshu Mathur

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 27 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Poland 1 4%
Norway 1 4%
Unknown 25 93%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 22%
Student > Master 4 15%
Professor 4 15%
Student > Bachelor 4 15%
Other 3 11%
Other 6 22%
Readers by discipline Count As %
Economics, Econometrics and Finance 10 37%
Computer Science 7 26%
Arts and Humanities 2 7%
Engineering 2 7%
Agricultural and Biological Sciences 1 4%
Other 4 15%
Unknown 1 4%
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 01 July 2015.
All research outputs
#15,340,005
of 22,817,213 outputs
Outputs from Computational Economics
#114
of 190 outputs
Outputs of similar age
#94,394
of 136,137 outputs
Outputs of similar age from Computational Economics
#3
of 3 outputs
Altmetric has tracked 22,817,213 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 190 research outputs from this source. They receive a mean Attention Score of 3.9. This one is in the 23rd percentile – i.e., 23% 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 136,137 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 18th percentile – i.e., 18% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 3 others from the same source and published within six weeks on either side of this one.