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Identification of piecewise affine systems via mixed-integer programming

Overview of attention for article published in Automatica, January 2004
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Mentioned by

patent
2 patents

Citations

dimensions_citation
315 Dimensions

Readers on

mendeley
111 Mendeley
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Title
Identification of piecewise affine systems via mixed-integer programming
Published in
Automatica, January 2004
DOI 10.1016/j.automatica.2003.08.006
Authors

Jacob Roll, Alberto Bemporad, Lennart Ljung

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 111 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 4 4%
Chile 1 <1%
France 1 <1%
United Kingdom 1 <1%
Brazil 1 <1%
Canada 1 <1%
Slovakia 1 <1%
Unknown 101 91%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 34 31%
Student > Master 16 14%
Professor > Associate Professor 14 13%
Researcher 12 11%
Professor 7 6%
Other 19 17%
Unknown 9 8%
Readers by discipline Count As %
Engineering 64 58%
Computer Science 18 16%
Mathematics 5 5%
Business, Management and Accounting 3 3%
Agricultural and Biological Sciences 1 <1%
Other 5 5%
Unknown 15 14%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 04 September 2018.
All research outputs
#8,534,528
of 25,371,288 outputs
Outputs from Automatica
#146
of 1,096 outputs
Outputs of similar age
#36,568
of 143,822 outputs
Outputs of similar age from Automatica
#1
of 8 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,096 research outputs from this source. They receive a mean Attention Score of 2.4. This one has gotten more attention than average, scoring higher than 52% 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 143,822 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 16th percentile – i.e., 16% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 8 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