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Like-attracts-like optimizer-based video robotics clustering control design for power device monitoring and inspection

Overview of attention for article published in Frontiers in Energy Research, January 2023
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Title
Like-attracts-like optimizer-based video robotics clustering control design for power device monitoring and inspection
Published in
Frontiers in Energy Research, January 2023
DOI 10.3389/fenrg.2022.1030034
Authors

Xuyong Huang, Biao Tang, Mengmeng Zhu, Yutang Ma, Xianlong Ma, Lijun Tang, Xin Wang, Dongdong Zhu

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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 17 January 2023.
All research outputs
#20,925,547
of 23,556,846 outputs
Outputs from Frontiers in Energy Research
#1,363
of 3,599 outputs
Outputs of similar age
#344,837
of 435,569 outputs
Outputs of similar age from Frontiers in Energy Research
#63
of 384 outputs
Altmetric has tracked 23,556,846 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,599 research outputs from this source. They receive a mean Attention Score of 1.7. This one is in the 1st percentile – i.e., 1% 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 435,569 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 384 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.