↓ Skip to main content

Optimal Sizing Grid-Connected Hybrid PV/Generator/Battery Systems Following the Prediction of CO2 Emission and Electricity Consumption by Machine Learning Methods (MLP and SVR): Aseer, Tabuk, and…

Overview of attention for article published in Frontiers in Energy Research, April 2022
Altmetric Badge

About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • High Attention Score compared to outputs of the same age and source (93rd percentile)

Mentioned by

twitter
3 X users

Citations

dimensions_citation
6 Dimensions

Readers on

mendeley
18 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Optimal Sizing Grid-Connected Hybrid PV/Generator/Battery Systems Following the Prediction of CO2 Emission and Electricity Consumption by Machine Learning Methods (MLP and SVR): Aseer, Tabuk, and Eastern Region, Saudi Arabia
Published in
Frontiers in Energy Research, April 2022
DOI 10.3389/fenrg.2022.879373
Authors

Khalid Almutairi, Mubarak Almutairi, Kamal Harb, Omar Marey

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

Geographical breakdown

Country Count As %
Unknown 18 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 3 17%
Other 3 17%
Student > Ph. D. Student 2 11%
Unspecified 1 6%
Student > Bachelor 1 6%
Other 0 0%
Unknown 8 44%
Readers by discipline Count As %
Energy 4 22%
Engineering 3 17%
Computer Science 2 11%
Unspecified 1 6%
Unknown 8 44%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 25 April 2022.
All research outputs
#16,432,063
of 25,173,778 outputs
Outputs from Frontiers in Energy Research
#485
of 4,411 outputs
Outputs of similar age
#241,135
of 437,018 outputs
Outputs of similar age from Frontiers in Energy Research
#31
of 479 outputs
Altmetric has tracked 25,173,778 research outputs across all sources so far. This one is in the 34th percentile – i.e., 34% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,411 research outputs from this source. They receive a mean Attention Score of 1.6. This one has done well, scoring higher than 88% 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 437,018 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 44th percentile – i.e., 44% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 479 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 93% of its contemporaries.