Predictive maintenance applied to mission critical supercomputing environments: remaining useful life estimation of a hydraulic cooling system using deep learning
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 18 October 2022.
All research outputs
#16,223,992
of 23,911,072 outputs
Outputs from The Journal of Supercomputing
#338
of 543 outputs
Outputs of similar age
#242,716
of 424,435 outputs
Outputs of similar age from The Journal of Supercomputing
#4
of 11 outputs
Altmetric has tracked 23,911,072 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 543 research outputs from this source. They receive a mean Attention Score of 2.9. This one is in the 20th percentile – i.e., 20% 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 424,435 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 11 others from the same source and published within six weeks on either side of this one. This one is in the 18th percentile – i.e., 18% of its contemporaries scored the same or lower than it.
