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AutoML-GWL: Automated machine learning model for the prediction of groundwater level

Overview of attention for article published in Engineering Applications of Artificial Intelligence, January 2024
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#15 of 819)
  • High Attention Score compared to outputs of the same age (91st percentile)
  • High Attention Score compared to outputs of the same age and source (95th percentile)

Mentioned by

twitter
30 X users

Citations

dimensions_citation
8 Dimensions

Readers on

mendeley
35 Mendeley
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Title
AutoML-GWL: Automated machine learning model for the prediction of groundwater level
Published in
Engineering Applications of Artificial Intelligence, January 2024
DOI 10.1016/j.engappai.2023.107405
Authors

Abhilash Singh, Sharad Patel, Vipul Bhadani, Vaibhav Kumar, Kumar Gaurav

X Demographics

X Demographics

The data shown below were collected from the profiles of 30 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 35 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 35 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 4 11%
Student > Master 4 11%
Student > Doctoral Student 2 6%
Researcher 2 6%
Student > Ph. D. Student 2 6%
Other 5 14%
Unknown 16 46%
Readers by discipline Count As %
Engineering 6 17%
Computer Science 5 14%
Unspecified 4 11%
Environmental Science 1 3%
Unknown 19 54%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 19. 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 03 January 2024.
All research outputs
#2,016,332
of 25,866,425 outputs
Outputs from Engineering Applications of Artificial Intelligence
#15
of 819 outputs
Outputs of similar age
#30,876
of 359,930 outputs
Outputs of similar age from Engineering Applications of Artificial Intelligence
#1
of 24 outputs
Altmetric has tracked 25,866,425 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 819 research outputs from this source. They receive a mean Attention Score of 3.3. This one has done particularly well, scoring higher than 98% 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 359,930 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 91% of its contemporaries.
We're also able to compare this research output to 24 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 95% of its contemporaries.