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Machine Learning and Metaheuristic Methods for Renewable Power Forecasting: A Recent Review

Overview of attention for article published in Frontiers in Chemical Engineering, April 2021
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About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • Good Attention Score compared to outputs of the same age and source (66th percentile)

Mentioned by

twitter
3 X users

Citations

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30 Dimensions

Readers on

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65 Mendeley
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Title
Machine Learning and Metaheuristic Methods for Renewable Power Forecasting: A Recent Review
Published in
Frontiers in Chemical Engineering, April 2021
DOI 10.3389/fceng.2021.665415
Authors

Hanin Alkabbani, Ali Ahmadian, Qinqin Zhu, Ali Elkamel

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.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 65 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 65 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 10 15%
Researcher 6 9%
Unspecified 3 5%
Lecturer 3 5%
Student > Master 3 5%
Other 9 14%
Unknown 31 48%
Readers by discipline Count As %
Engineering 10 15%
Computer Science 6 9%
Chemical Engineering 5 8%
Energy 4 6%
Business, Management and Accounting 2 3%
Other 7 11%
Unknown 31 48%
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 13 May 2021.
All research outputs
#15,685,238
of 23,308,124 outputs
Outputs from Frontiers in Chemical Engineering
#85
of 269 outputs
Outputs of similar age
#259,957
of 436,647 outputs
Outputs of similar age from Frontiers in Chemical Engineering
#7
of 21 outputs
Altmetric has tracked 23,308,124 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 269 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 436,647 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 30th percentile – i.e., 30% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 21 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 66% of its contemporaries.