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Auto-Switch Gaussian Process Regression-Based Probabilistic Soft Sensors for Industrial Multigrade Processes with Transitions

Overview of attention for article published in Industrial & Engineering Chemistry Research, May 2015
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (62nd percentile)
  • Good Attention Score compared to outputs of the same age and source (78th percentile)

Mentioned by

twitter
1 X user
patent
2 patents

Readers on

mendeley
24 Mendeley
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Article details
Title
Auto-Switch Gaussian Process Regression-Based Probabilistic Soft Sensors for Industrial Multigrade Processes with Transitions
Published in
Industrial & Engineering Chemistry Research, May 2015
DOI 10.1021/ie504185j
Authors

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Timeline Attention over time Attention Score history
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Activity
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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 demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 24 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
United States 1 4%
Unknown 23 96%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Ph. D. Student 6 25%
Student > Master 5 21%
Student > Bachelor 2 8%
Professor 2 8%
Student > Postgraduate 2 8%
Other 3 13%
Unknown 4 17%
Readers by discipline
Readers by discipline Count As %
Chemical Engineering 5 21%
Engineering 4 17%
Mathematics 2 8%
Agricultural and Biological Sciences 2 8%
Environmental Science 1 4%
Other 2 8%
Unknown 8 33%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 26 October 2021.
All research outputs
#11,336,372
of 33,493,714 outputs
Outputs from Industrial & Engineering Chemistry Research
#2,828
of 20,334 outputs
Outputs of similar age
#108,682
of 302,569 outputs
Outputs of similar age from Industrial & Engineering Chemistry Research
#24
of 290 outputs
Altmetric has tracked 33,493,714 research outputs across all sources so far. This one has received more attention than most of these and is in the 64th percentile.
So far Altmetric has tracked 20,334 research outputs from this source. They receive a mean Attention Score of 2.3. This one has done well, scoring higher than 80% 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 302,569 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 62% of its contemporaries.
We're also able to compare this research output to 290 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 78% of its contemporaries.