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A Fault Diagnosis Method for Lithium-Ion Battery Packs Using Improved RBF Neural Network

Overview of attention for article published in Frontiers in Energy Research, August 2021
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About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • High Attention Score compared to outputs of the same age and source (83rd percentile)

Mentioned by

twitter
3 X users

Citations

dimensions_citation
36 Dimensions

Readers on

mendeley
33 Mendeley
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Title
A Fault Diagnosis Method for Lithium-Ion Battery Packs Using Improved RBF Neural Network
Published in
Frontiers in Energy Research, August 2021
DOI 10.3389/fenrg.2021.702139
Authors

Jia Wang, Shenglong Zhang, Xia Hu

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.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 33 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 33 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 15%
Other 2 6%
Student > Doctoral Student 2 6%
Student > Bachelor 2 6%
Researcher 2 6%
Other 3 9%
Unknown 17 52%
Readers by discipline Count As %
Engineering 7 21%
Energy 4 12%
Chemical Engineering 1 3%
Business, Management and Accounting 1 3%
Materials Science 1 3%
Other 1 3%
Unknown 18 55%
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 03 August 2021.
All research outputs
#15,686,478
of 23,310,485 outputs
Outputs from Frontiers in Energy Research
#585
of 3,446 outputs
Outputs of similar age
#250,483
of 432,227 outputs
Outputs of similar age from Frontiers in Energy Research
#27
of 220 outputs
Altmetric has tracked 23,310,485 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 3,446 research outputs from this source. They receive a mean Attention Score of 1.7. This one has done well, scoring higher than 81% 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 432,227 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 31st percentile – i.e., 31% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 220 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 83% of its contemporaries.