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Combustion Efficiency Optimization and Virtual Testing: A Data-Mining Approach

Overview of attention for article published in IEEE Transactions on Industrial Informatics, August 2006
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (68th percentile)

Mentioned by

patent
5 patents

Readers on

mendeley
35 Mendeley
citeulike
1 CiteULike
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Article details
Title
Combustion Efficiency Optimization and Virtual Testing: A Data-Mining Approach
Published in
IEEE Transactions on Industrial Informatics, August 2006
DOI 10.1109/tii.2006.873598
Authors

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Timeline Attention over time Attention Score history
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Activity
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Mendeley demographics

Mendeley demographics

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.
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Geographical breakdown

Geographical breakdown
Country Count As %
Spain 1 3%
Unknown 34 97%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Ph. D. Student 7 20%
Student > Master 6 17%
Researcher 6 17%
Professor > Associate Professor 4 11%
Other 3 9%
Other 4 11%
Unknown 5 14%
Readers by discipline
Readers by discipline Count As %
Engineering 17 49%
Computer Science 4 11%
Chemical Engineering 2 6%
Mathematics 1 3%
Business, Management and Accounting 1 3%
Other 1 3%
Unknown 9 26%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 14 August 2018.
All research outputs
#6,542,369
of 30,143,106 outputs
Outputs from IEEE Transactions on Industrial Informatics
#138
of 1,215 outputs
Outputs of similar age
#20,846
of 107,145 outputs
Outputs of similar age from IEEE Transactions on Industrial Informatics
#1
of 3 outputs
Altmetric has tracked 30,143,106 research outputs across all sources so far. This one has received more attention than most of these and is in the 74th percentile.
So far Altmetric has tracked 1,215 research outputs from this source. They receive a mean Attention Score of 4.4. This one has done well, scoring higher than 75% 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 107,145 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 68% of its contemporaries.
We're also able to compare this research output to 3 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them