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Modelling and Forecasting Fresh Agro-Food Commodity Consumption Per Capita in Malaysia Using Machine Learning

Overview of attention for article published in Mobile Information Systems, November 2022
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Mentioned by

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1 X user

Citations

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3 Dimensions

Readers on

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45 Mendeley
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Title
Modelling and Forecasting Fresh Agro-Food Commodity Consumption Per Capita in Malaysia Using Machine Learning
Published in
Mobile Information Systems, November 2022
DOI 10.1155/2022/6106557
Authors

Rayner Alfred, Christylyn Leikson, Bonaventure Boniface, Geoffrey Harvey Tanakinjal, Assis Kamu, Mori Kogid, Stephen L. Sondoh, Nolila Mohd Nawi, Nalini Arumugam, Ryan Macdonell Andrias

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 45 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 45 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 3 7%
Lecturer > Senior Lecturer 2 4%
Unspecified 2 4%
Student > Master 2 4%
Student > Postgraduate 2 4%
Other 4 9%
Unknown 30 67%
Readers by discipline Count As %
Business, Management and Accounting 3 7%
Computer Science 3 7%
Engineering 3 7%
Agricultural and Biological Sciences 3 7%
Unspecified 2 4%
Other 2 4%
Unknown 29 64%
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 22 November 2022.
All research outputs
#20,673,680
of 25,392,582 outputs
Outputs from Mobile Information Systems
#207
of 292 outputs
Outputs of similar age
#320,672
of 434,894 outputs
Outputs of similar age from Mobile Information Systems
#7
of 14 outputs
Altmetric has tracked 25,392,582 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 292 research outputs from this source. They receive a mean Attention Score of 2.6. This one is in the 10th percentile – i.e., 10% 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 434,894 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 14th percentile – i.e., 14% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 14 others from the same source and published within six weeks on either side of this one. This one is in the 21st percentile – i.e., 21% of its contemporaries scored the same or lower than it.