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Applications of Machine Learning to Wind Engineering

Overview of attention for article published in Frontiers in Built Environment, March 2022
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About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • Above-average Attention Score compared to outputs of the same age and source (59th percentile)

Mentioned by

twitter
3 X users

Citations

dimensions_citation
25 Dimensions

Readers on

mendeley
52 Mendeley
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Title
Applications of Machine Learning to Wind Engineering
Published in
Frontiers in Built Environment, March 2022
DOI 10.3389/fbuil.2022.811460
Authors

Teng Wu, Reda Snaiki

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 X users 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 52 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 52 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 12%
Student > Doctoral Student 4 8%
Researcher 4 8%
Other 2 4%
Unspecified 2 4%
Other 6 12%
Unknown 28 54%
Readers by discipline Count As %
Engineering 9 17%
Unspecified 2 4%
Earth and Planetary Sciences 2 4%
Business, Management and Accounting 1 2%
Agricultural and Biological Sciences 1 2%
Other 6 12%
Unknown 31 60%
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 January 2023.
All research outputs
#15,825,082
of 23,509,253 outputs
Outputs from Frontiers in Built Environment
#364
of 1,115 outputs
Outputs of similar age
#254,583
of 444,461 outputs
Outputs of similar age from Frontiers in Built Environment
#26
of 69 outputs
Altmetric has tracked 23,509,253 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 1,115 research outputs from this source. They receive a mean Attention Score of 3.0. This one has gotten more attention than average, scoring higher than 64% 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 444,461 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 32nd percentile – i.e., 32% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 69 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 59% of its contemporaries.