| Title |
Extreme learning machines: a survey
|
|---|---|
| Published in |
International Journal of Machine Learning and Cybernetics, May 2011
|
| DOI | 10.1007/s13042-011-0019-y |
| Authors |
Guang-Bin Huang, Dian Hui Wang, Yuan Lan |
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.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 717 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Brazil | 5 | <1% |
| China | 4 | <1% |
| United States | 3 | <1% |
| United Kingdom | 3 | <1% |
| Germany | 2 | <1% |
| Japan | 2 | <1% |
| Canada | 2 | <1% |
| Italy | 2 | <1% |
| Australia | 2 | <1% |
| Other | 12 | 2% |
| Unknown | 680 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 173 | 24% |
| Student > Master | 123 | 17% |
| Researcher | 81 | 11% |
| Professor > Associate Professor | 40 | 6% |
| Student > Doctoral Student | 38 | 5% |
| Other | 121 | 17% |
| Unknown | 141 | 20% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 257 | 36% |
| Engineering | 169 | 24% |
| Mathematics | 14 | 2% |
| Earth and Planetary Sciences | 12 | 2% |
| Physics and Astronomy | 11 | 2% |
| Other | 71 | 10% |
| Unknown | 183 | 26% |
Attention Score in Context
This research output has an Altmetric Attention Score of 13. 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 15 March 2022.
All research outputs
#2,647,134
of 25,006,193 outputs
Outputs from International Journal of Machine Learning and Cybernetics
#2
of 570 outputs
Outputs of similar age
#12,059
of 117,298 outputs
Outputs of similar age from International Journal of Machine Learning and Cybernetics
#1
of 1 outputs
Altmetric has tracked 25,006,193 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 570 research outputs from this source. They receive a mean Attention Score of 1.2. This one has done particularly well, scoring higher than 99% 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 117,298 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 89% of its contemporaries.
We're also able to compare this research output to 1 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