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Accurate Classification of EEG Signals Using Neural Networks Trained by Hybrid Population-physic-based Algorithm

Overview of attention for article published in Machine Intelligence Research, November 2018
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1 X user

Citations

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36 Dimensions

Readers on

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31 Mendeley
Title
Accurate Classification of EEG Signals Using Neural Networks Trained by Hybrid Population-physic-based Algorithm
Published in
Machine Intelligence Research, November 2018
DOI 10.1007/s11633-018-1158-3
Authors

Sajjad Afrakhteh, Mohammad-Reza Mosavi, Mohammad Khishe, Ahmad Ayatollahi

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 readers

Mendeley readers

The data shown below were compiled from readership statistics for 31 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 31 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 7 23%
Student > Master 4 13%
Researcher 3 10%
Student > Doctoral Student 2 6%
Professor > Associate Professor 2 6%
Other 1 3%
Unknown 12 39%
Readers by discipline Count As %
Engineering 9 29%
Computer Science 4 13%
Agricultural and Biological Sciences 1 3%
Physics and Astronomy 1 3%
Mathematics 1 3%
Other 0 0%
Unknown 15 48%
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 March 2020.
All research outputs
#20,663,600
of 25,385,509 outputs
Outputs from Machine Intelligence Research
#228
of 444 outputs
Outputs of similar age
#285,382
of 365,313 outputs
Outputs of similar age from Machine Intelligence Research
#5
of 21 outputs
Altmetric has tracked 25,385,509 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
So far Altmetric has tracked 444 research outputs from this source. They receive a mean Attention Score of 2.5. This one is in the 1st percentile – i.e., 1% 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 365,313 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 12th percentile – i.e., 12% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 21 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.