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Attention Score in Context
Title |
Nature Inspired Computing: An Overview and Some Future Directions
|
---|---|
Published in |
Cognitive Computation, November 2015
|
DOI | 10.1007/s12559-015-9370-8 |
Pubmed ID | |
Authors |
Nazmul Siddique, Hojjat Adeli |
Abstract |
This paper presents an overview of significant advances made in the emerging field of nature-inspired computing (NIC) with a focus on the physics- and biology-based approaches and algorithms. A parallel development in the past two decades has been the emergence of the field of computational intelligence (CI) consisting primarily of the three fields of neural networks, evolutionary computing and fuzzy logic. It is observed that NIC and CI intersect. The authors advocate and foresee more cross-fertilisation of the two emerging fields. |
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.
Geographical breakdown
Country | Count | As % |
---|---|---|
Netherlands | 1 | 100% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 168 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Hong Kong | 1 | <1% |
Spain | 1 | <1% |
Unknown | 166 | 99% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 35 | 21% |
Student > Master | 21 | 13% |
Researcher | 10 | 6% |
Student > Bachelor | 9 | 5% |
Student > Doctoral Student | 7 | 4% |
Other | 32 | 19% |
Unknown | 54 | 32% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 50 | 30% |
Engineering | 39 | 23% |
Business, Management and Accounting | 2 | 1% |
Decision Sciences | 2 | 1% |
Medicine and Dentistry | 2 | 1% |
Other | 10 | 6% |
Unknown | 63 | 38% |
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 31 May 2020.
All research outputs
#17,778,101
of 22,834,308 outputs
Outputs from Cognitive Computation
#192
of 413 outputs
Outputs of similar age
#263,262
of 387,537 outputs
Outputs of similar age from Cognitive Computation
#5
of 10 outputs
Altmetric has tracked 22,834,308 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 413 research outputs from this source. They receive a mean Attention Score of 2.3. This one is in the 46th percentile – i.e., 46% 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 387,537 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 10 others from the same source and published within six weeks on either side of this one. This one has scored higher than 5 of them.