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A Short-Term Wind Power Forecast Method via XGBoost Hyper-Parameters Optimization

Overview of attention for article published in Frontiers in Energy Research, May 2022
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1 X user

Citations

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22 Dimensions

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23 Mendeley
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Title
A Short-Term Wind Power Forecast Method via XGBoost Hyper-Parameters Optimization
Published in
Frontiers in Energy Research, May 2022
DOI 10.3389/fenrg.2022.905155
Authors

Xiong Xiong, Xiaojie Guo, Pingliang Zeng, Ruiling Zou, Xiaolong 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 23 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 23 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 4 17%
Student > Ph. D. Student 4 17%
Lecturer 2 9%
Student > Bachelor 1 4%
Student > Doctoral Student 1 4%
Other 2 9%
Unknown 9 39%
Readers by discipline Count As %
Engineering 5 22%
Unspecified 4 17%
Computer Science 3 13%
Economics, Econometrics and Finance 2 9%
Unknown 9 39%
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 10 June 2022.
All research outputs
#20,137,012
of 22,641,687 outputs
Outputs from Frontiers in Energy Research
#1,269
of 3,143 outputs
Outputs of similar age
#355,852
of 436,501 outputs
Outputs of similar age from Frontiers in Energy Research
#80
of 447 outputs
Altmetric has tracked 22,641,687 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 3,143 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 436,501 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 447 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.