Brunel University Research Archive(BURA) preserves and enables easy and open access to all
types of digital content. It showcases Brunel's research outputs.
Research contained within BURA is open access, although some publications may be subject
to publisher imposed embargoes. All awarded PhD theses are also archived on BURA.
Please use this identifier to cite or link to this item:
http://bura.brunel.ac.uk/handle/2438/17871Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Angelides, MC | - |
| dc.contributor.author | Almalki, FA | - |
| dc.date.accessioned | 2019-04-08T11:17:14Z | - |
| dc.date.available | 2019-04-08T11:17:14Z | - |
| dc.date.issued | 2019 | - |
| dc.identifier.citation | Computer Communications | en_US |
| dc.identifier.issn | 0140-3664 | - |
| dc.identifier.uri | http://bura.brunel.ac.uk/handle/2438/17871 | - |
| dc.language.iso | en | en_US |
| dc.publisher | Elsevier | en_US |
| dc.subject | Propagation models | en_US |
| dc.subject | Low Altitude Platforms | en_US |
| dc.subject | Machine learning | en_US |
| dc.title | A Machine Learning Approach to Evolving an Optimal Propagation Model for Last Mile Connectivity using Low Altitude Platforms | en_US |
| dc.type | Article | en_US |
| dc.relation.isPartOf | Computer Communications | - |
| pubs.publication-status | Accepted | - |
| Appears in Collections: | Dept of Electronic and Electrical Engineering Embargoed Research Papers | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| FullText.pdf | Embargoed until 15-06-2021 | 3.71 MB | Adobe PDF | View/Open |
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