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Machine learning model and strategy for fast and accurate detection of leaks in water supply network

Overview of attention for article published in Journal of Infrastructure Preservation and Resilience, April 2021
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Mentioned by

twitter
1 tweeter

Citations

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2 Dimensions

Readers on

mendeley
15 Mendeley
Title
Machine learning model and strategy for fast and accurate detection of leaks in water supply network
Published in
Journal of Infrastructure Preservation and Resilience, April 2021
DOI 10.1186/s43065-021-00021-6
Authors

Xudong Fan, Xijin Zhang, Xiong ( Bill) Yu

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 15 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 15 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 33%
Student > Bachelor 3 20%
Researcher 2 13%
Student > Master 1 7%
Student > Doctoral Student 1 7%
Other 0 0%
Unknown 3 20%
Readers by discipline Count As %
Engineering 9 60%
Computer Science 1 7%
Arts and Humanities 1 7%
Unknown 4 27%

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 15 April 2021.
All research outputs
#15,294,715
of 19,097,846 outputs
Outputs from Journal of Infrastructure Preservation and Resilience
#15
of 34 outputs
Outputs of similar age
#236,132
of 327,968 outputs
Outputs of similar age from Journal of Infrastructure Preservation and Resilience
#1
of 1 outputs
Altmetric has tracked 19,097,846 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 34 research outputs from this source. They receive a mean Attention Score of 1.1. This one scored the same or higher as 19 of them.
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 327,968 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 18th percentile – i.e., 18% of its contemporaries scored the same or lower than it.
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