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Flood Susceptibility Modeling in a Subtropical Humid Low-Relief Alluvial Plain Environment: Application of Novel Ensemble Machine Learning Approach

Overview of attention for article published in Frontiers in Earth Science, December 2021
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  • Average Attention Score compared to outputs of the same age
  • Good Attention Score compared to outputs of the same age and source (69th percentile)

Mentioned by

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3 X users

Citations

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31 Dimensions

Readers on

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57 Mendeley
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Title
Flood Susceptibility Modeling in a Subtropical Humid Low-Relief Alluvial Plain Environment: Application of Novel Ensemble Machine Learning Approach
Published in
Frontiers in Earth Science, December 2021
DOI 10.3389/feart.2021.659296
Authors

Manish Pandey, Aman Arora, Alireza Arabameri, Romulus Costache, Naveen Kumar, Varun Narayan Mishra, Hoang Nguyen, Jagriti Mishra, Masood Ahsan Siddiqui, Yogesh Ray, Sangeeta Soni, Shukla

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 57 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 57 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 8 14%
Student > Ph. D. Student 7 12%
Student > Master 6 11%
Other 3 5%
Lecturer 2 4%
Other 6 11%
Unknown 25 44%
Readers by discipline Count As %
Engineering 11 19%
Earth and Planetary Sciences 10 18%
Environmental Science 3 5%
Unspecified 2 4%
Agricultural and Biological Sciences 2 4%
Other 4 7%
Unknown 25 44%
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 03 January 2022.
All research outputs
#15,333,503
of 22,805,349 outputs
Outputs from Frontiers in Earth Science
#1,824
of 4,489 outputs
Outputs of similar age
#276,075
of 497,148 outputs
Outputs of similar age from Frontiers in Earth Science
#113
of 447 outputs
Altmetric has tracked 22,805,349 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 4,489 research outputs from this source. They receive a mean Attention Score of 5.0. This one has gotten more attention than average, scoring higher than 55% 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 497,148 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 32nd percentile – i.e., 32% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 447 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 69% of its contemporaries.