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A hybrid RNN-GPOD surrogate model for real-time settlement predictions in mechanised tunnelling

Overview of attention for article published in Advanced Modeling and Simulation in Engineering Sciences, March 2016
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About this Attention Score

  • Average Attention Score compared to outputs of the same age

Mentioned by

peer_reviews
1 peer review site

Citations

dimensions_citation
38 Dimensions

Readers on

mendeley
39 Mendeley
Title
A hybrid RNN-GPOD surrogate model for real-time settlement predictions in mechanised tunnelling
Published in
Advanced Modeling and Simulation in Engineering Sciences, March 2016
DOI 10.1186/s40323-016-0057-9
Authors

Ba-Trung Cao, Steffen Freitag, Günther Meschke

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 39 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 1 3%
Unknown 38 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 10 26%
Researcher 6 15%
Other 3 8%
Student > Master 3 8%
Professor 3 8%
Other 6 15%
Unknown 8 21%
Readers by discipline Count As %
Engineering 19 49%
Computer Science 5 13%
Mathematics 1 3%
Physics and Astronomy 1 3%
Environmental Science 1 3%
Other 0 0%
Unknown 12 31%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 May 2018.
All research outputs
#15,488,947
of 23,016,919 outputs
Outputs from Advanced Modeling and Simulation in Engineering Sciences
#24
of 61 outputs
Outputs of similar age
#178,303
of 299,433 outputs
Outputs of similar age from Advanced Modeling and Simulation in Engineering Sciences
#2
of 2 outputs
Altmetric has tracked 23,016,919 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 61 research outputs from this source. They receive a mean Attention Score of 2.0. This one is in the 37th percentile – i.e., 37% 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 299,433 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 31st percentile – i.e., 31% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 2 others from the same source and published within six weeks on either side of this one.