| dc.contributor.author | Hemberg, Erik | |
| dc.contributor.author | Ho, Lester | |
| dc.contributor.author | O'Neill, Michael | |
| dc.contributor.author | Claussen, Holger | |
| dc.date.accessioned | 2012-02-16T12:03:30Z | |
| dc.date.available | 2012-02-16T12:03:30Z | |
| dc.date.copyright | 2011 ACM | en |
| dc.date.issued | 2011 | |
| dc.identifier.isbn | 978-1-4503-0690-4 | |
| dc.identifier.uri | http://hdl.handle.net/10197/3511 | |
| dc.description | Paper presented at the ACM Genetic and Evolutionary Computation Conference GECCO 2011 Symbolic Regression and Modelling Workshop, Dublin, Ireland, 12-16, July | en |
| dc.description.abstract | We present a novel application of Grammatical Evolution to the real-world application of femtocell coverage. A symbolic regression approach is adopted in which we wish to uncover an expression to automatically manage the power settings of individual femtocells in a larger femtocell group to optimise the coverage of the network under time varying load. The generation of symbolic expressions is important as it facilitates the analysis of the evolved solutions. Given the multi-objective nature of the problem we hybridise Grammatical Evolution with NSGA-II connected to tabu search. The best evolved solutions have superior power consumption characteristics than a fixed coverage femtocell deployment. | en |
| dc.description.sponsorship | Science Foundation Ireland | en |
| dc.description.uri | Conference website | en |
| dc.description.uri | http://www.sigevo.org/gecco-2011/ | en |
| dc.format.extent | 2491337 bytes | |
| dc.format.mimetype | application/pdf | |
| dc.language.iso | en | en |
| dc.publisher | ACM | en |
| dc.relation.ispartof | GECCO '11 : Proceedings of the 13th annual conference companion on Genetic and evolutionary computation | en |
| dc.relation.requires | CASL Research Collection | en |
| dc.rights | This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in the GECCO '11 Proceedings of the 13th annual conference companion on Genetic and evolutionary computation http://doi.acm.org/10.1145/2001858.2002061 | en |
| dc.subject | Femtocell | en |
| dc.subject | Grammatical evolution | en |
| dc.subject | Symbolic regression | en |
| dc.subject | Wireless networks | en |
| dc.subject.lcsh | Femtocells | en |
| dc.subject.lcsh | Evolutionary computation | en |
| dc.subject.lcsh | Wireless sensor networks | en |
| dc.title | A symbolic regression approach to manage femtocell coverage using grammatical genetic programming | en |
| dc.type | Conference Publication | en |
| dc.internal.availability | Full text available | en |
| dc.internal.webversions | Publisher's version | en |
| dc.internal.webversions | http://doi.acm.org/10.1145/2001858.2002061 | en |
| dc.status | Peer reviewed | en |
| dc.identifier.doi | 10.1145/2001858.2002061 | |
| dc.neeo.contributor | Hemberg|Erik|aut| | en |
| dc.neeo.contributor | Ho|Lester|aut| | en |
| dc.neeo.contributor | O'Neill|Michael|aut| | en |
| dc.neeo.contributor | Claussen|Holger|aut| | en |
| dc.description.admin | ti, ke, ab, co, li - TS 02.12 | en |
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