| Title |
Hybrid of genetic algorithm and local search to solve MAX-SAT problem using nVidia CUDA framework
|
|---|---|
| Published in |
Genetic Programming and Evolvable Machines, October 2009
|
| DOI | 10.1007/s10710-009-9091-4 |
| Authors |
Asim Munawar, Mohamed Wahib, Masaharu Munetomo, Kiyoshi Akama |
Mendeley readers
The data shown below were compiled from readership statistics for 63 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Italy | 2 | 3% |
| United Kingdom | 1 | 2% |
| China | 1 | 2% |
| Brazil | 1 | 2% |
| Unknown | 58 | 92% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 19 | 30% |
| Student > Ph. D. Student | 12 | 19% |
| Researcher | 8 | 13% |
| Student > Bachelor | 7 | 11% |
| Professor | 4 | 6% |
| Other | 7 | 11% |
| Unknown | 6 | 10% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 45 | 71% |
| Engineering | 4 | 6% |
| Mathematics | 1 | 2% |
| Biochemistry, Genetics and Molecular Biology | 1 | 2% |
| Social Sciences | 1 | 2% |
| Other | 1 | 2% |
| Unknown | 10 | 16% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 07 January 2020.
All research outputs
#7,552,525
of 23,039,416 outputs
Outputs from Genetic Programming and Evolvable Machines
#42
of 120 outputs
Outputs of similar age
#33,894
of 94,370 outputs
Outputs of similar age from Genetic Programming and Evolvable Machines
#1
of 3 outputs
Altmetric has tracked 23,039,416 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 120 research outputs from this source. They receive a mean Attention Score of 3.5. This one is in the 47th percentile – i.e., 47% 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 94,370 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 20th percentile – i.e., 20% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 3 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