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Application of Multi-Objective Genetic Algorithm Based Simulation for Cost-Effective Building Energy Efficiency Design and Thermal Comfort Improvement

Overview of attention for article published in Frontiers in Energy Research, April 2018
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Mentioned by

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2 X users

Citations

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26 Dimensions

Readers on

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65 Mendeley
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Title
Application of Multi-Objective Genetic Algorithm Based Simulation for Cost-Effective Building Energy Efficiency Design and Thermal Comfort Improvement
Published in
Frontiers in Energy Research, April 2018
DOI 10.3389/fenrg.2018.00025
Authors

Yaolin Lin, Wei Yang

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 X users 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 65 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 65 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 14 22%
Student > Ph. D. Student 9 14%
Student > Doctoral Student 7 11%
Researcher 5 8%
Lecturer 3 5%
Other 7 11%
Unknown 20 31%
Readers by discipline Count As %
Engineering 17 26%
Energy 7 11%
Computer Science 4 6%
Decision Sciences 2 3%
Arts and Humanities 2 3%
Other 6 9%
Unknown 27 42%
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 05 April 2018.
All research outputs
#18,600,232
of 23,039,416 outputs
Outputs from Frontiers in Energy Research
#746
of 3,302 outputs
Outputs of similar age
#256,074
of 329,678 outputs
Outputs of similar age from Frontiers in Energy Research
#17
of 34 outputs
Altmetric has tracked 23,039,416 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 3,302 research outputs from this source. They receive a mean Attention Score of 1.7. This one has gotten more attention than average, scoring higher than 60% 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 329,678 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 11th percentile – i.e., 11% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 34 others from the same source and published within six weeks on either side of this one. This one is in the 11th percentile – i.e., 11% of its contemporaries scored the same or lower than it.