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A scalable approach based on deep learning for big data time series forecasting

Overview of attention for article published in Integrated Computer-Aided Engineering, September 2018
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About this Attention Score

  • Among the highest-scoring outputs from this source (#27 of 113)
  • Average Attention Score compared to outputs of the same age

Mentioned by

patent
1 patent

Readers on

mendeley
78 Mendeley
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Article details
Title
A scalable approach based on deep learning for big data time series forecasting
Published in
Integrated Computer-Aided Engineering, September 2018
DOI 10.3233/ica-180580
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 78 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 %
Unknown 78 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Master 12 15%
Researcher 9 12%
Student > Ph. D. Student 6 8%
Student > Doctoral Student 5 6%
Lecturer 3 4%
Other 10 13%
Unknown 33 42%
Readers by discipline
Readers by discipline Count As %
Computer Science 18 23%
Engineering 11 14%
Economics, Econometrics and Finance 2 3%
Earth and Planetary Sciences 2 3%
Pharmacology, Toxicology and Pharmaceutical Science 1 1%
Other 6 8%
Unknown 38 49%
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 13 October 2026.
All research outputs
#12,469,414
of 34,652,893 outputs
Outputs from Integrated Computer-Aided Engineering
#27
of 113 outputs
Outputs of similar age
#157,135
of 376,810 outputs
Outputs of similar age from Integrated Computer-Aided Engineering
#3
of 3 outputs
Altmetric has tracked 34,652,893 research outputs across all sources so far. This one is in the 38th percentile – i.e., 38% of other outputs scored the same or lower than it.
So far Altmetric has tracked 113 research outputs from this source. They receive a mean Attention Score of 4.1. This one is in the 19th percentile – i.e., 19% of its peers scored the same or lower than it.
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 376,810 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 43rd percentile – i.e., 43% of its contemporaries scored the same or lower than it.
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.