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Deep Neural Network and Monte Carlo Tree Search applied to Fluid-Structure Topology Optimization

Overview of attention for article published in Scientific Reports, November 2019
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (74th percentile)
  • Good Attention Score compared to outputs of the same age and source (72nd percentile)

Mentioned by

news
1 news outlet

Citations

dimensions_citation
19 Dimensions

Readers on

mendeley
40 Mendeley
Title
Deep Neural Network and Monte Carlo Tree Search applied to Fluid-Structure Topology Optimization
Published in
Scientific Reports, November 2019
DOI 10.1038/s41598-019-51111-1
Pubmed ID
Authors

Audrey Gaymann, Francesco Montomoli

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 40 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 40 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 14 35%
Student > Master 7 18%
Professor > Associate Professor 3 8%
Student > Doctoral Student 2 5%
Professor 2 5%
Other 3 8%
Unknown 9 23%
Readers by discipline Count As %
Engineering 18 45%
Materials Science 3 8%
Physics and Astronomy 2 5%
Energy 2 5%
Computer Science 2 5%
Other 1 3%
Unknown 12 30%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 04 November 2020.
All research outputs
#4,278,872
of 23,257,423 outputs
Outputs from Scientific Reports
#33,647
of 125,724 outputs
Outputs of similar age
#87,880
of 364,945 outputs
Outputs of similar age from Scientific Reports
#1,114
of 4,142 outputs
Altmetric has tracked 23,257,423 research outputs across all sources so far. Compared to these this one has done well and is in the 80th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 125,724 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 18.3. This one has gotten more attention than average, scoring higher than 72% 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 364,945 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 74% of its contemporaries.
We're also able to compare this research output to 4,142 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 72% of its contemporaries.