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Generating adversarial deep reinforcement learning -based frequency control of Island City microgrid considering generalization of scenarios

Overview of attention for article published in Frontiers in Energy Research, March 2024
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  • Above-average Attention Score compared to outputs of the same age and source (52nd percentile)

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Title
Generating adversarial deep reinforcement learning -based frequency control of Island City microgrid considering generalization of scenarios
Published in
Frontiers in Energy Research, March 2024
DOI 10.3389/fenrg.2024.1377465
Authors

Houtianfu Wang, Zhecong Zhang, Qixin Wang

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 1 Mendeley reader of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 1 100%

Demographic breakdown

Readers by professional status Count As %
Other 1 100%
Readers by discipline Count As %
Computer Science 1 100%
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 15 March 2024.
All research outputs
#21,280,958
of 26,134,677 outputs
Outputs from Frontiers in Energy Research
#949
of 4,766 outputs
Outputs of similar age
#240,113
of 348,374 outputs
Outputs of similar age from Frontiers in Energy Research
#44
of 214 outputs
Altmetric has tracked 26,134,677 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 4,766 research outputs from this source. They receive a mean Attention Score of 1.6. This one has gotten more attention than average, scoring higher than 63% 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 348,374 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 18th percentile – i.e., 18% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 214 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 52% of its contemporaries.