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Deep learning-based solar power forecasting model to analyze a multi-energy microgrid energy system

Overview of attention for article published in Frontiers in Energy Research, March 2024
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  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
1 X user

Readers on

mendeley
6 Mendeley
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Title
Deep learning-based solar power forecasting model to analyze a multi-energy microgrid energy system
Published in
Frontiers in Energy Research, March 2024
DOI 10.3389/fenrg.2024.1363895
Authors

Sai Sasidhar Punyam Rajendran, Alemayehu Gebremedhin

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

Geographical breakdown

Country Count As %
Unknown 6 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 2 33%
Unspecified 1 17%
Researcher 1 17%
Student > Bachelor 1 17%
Unknown 1 17%
Readers by discipline Count As %
Chemical Engineering 1 17%
Unspecified 1 17%
Energy 1 17%
Engineering 1 17%
Unknown 2 33%
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 20 March 2024.
All research outputs
#21,309,356
of 26,168,182 outputs
Outputs from Frontiers in Energy Research
#963
of 4,782 outputs
Outputs of similar age
#238,728
of 346,958 outputs
Outputs of similar age from Frontiers in Energy Research
#41
of 203 outputs
Altmetric has tracked 26,168,182 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 4,782 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 62% 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 346,958 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 203 others from the same source and published within six weeks on either side of this one. This one is in the 43rd percentile – i.e., 43% of its contemporaries scored the same or lower than it.