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Rolling bearing fault diagnosis based on quantum LS-SVM

Overview of attention for article published in EPJ Quantum Technology , June 2022
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Mentioned by

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1 X user

Citations

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9 Dimensions

Readers on

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11 Mendeley
Title
Rolling bearing fault diagnosis based on quantum LS-SVM
Published in
EPJ Quantum Technology , June 2022
DOI 10.1140/epjqt/s40507-022-00137-y
Authors

Yuanyuan Li, Liyuan Song, Qichun Sun, Hua Xu, Xiaogang Li, Zhijun Fang, Wei Yao

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

Geographical breakdown

Country Count As %
Unknown 11 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 55%
Researcher 2 18%
Student > Bachelor 1 9%
Unknown 2 18%
Readers by discipline Count As %
Engineering 4 36%
Computer Science 2 18%
Energy 1 9%
Chemical Engineering 1 9%
Unknown 3 27%
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 2022.
All research outputs
#20,755,951
of 25,498,750 outputs
Outputs from EPJ Quantum Technology
#121
of 153 outputs
Outputs of similar age
#329,340
of 441,713 outputs
Outputs of similar age from EPJ Quantum Technology
#7
of 8 outputs
Altmetric has tracked 25,498,750 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 153 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.4. This one is in the 4th percentile – i.e., 4% 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 441,713 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 14th percentile – i.e., 14% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 8 others from the same source and published within six weeks on either side of this one.