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Is MO-CMA-ES superior to NSGA-II for the evolution of multi-objective neuro-controllers?

Author:
Moshaiov, A. , Abramovich, O.
Publisher:
IEEE
Year
: 2014
DOI: 10.1109/FENDT.2014.6928296
URI: http://libsearch.um.ac.ir:80/fum/handle/fum/1117052
Keyword(s): crack detection,eddy current testing,radiofrequency identification,RFID grids,TABS,UHF band,crack detection,health monitoring,radiofrequency identification tag antenna-based sensor,railway track,smart skin,structural health monitoring,ultrahigh frequency band,Metals,Monitoring,Radiofrequency identification,Resonant frequency,UHF antennas,NDT&,amp,E,RFID grids,crack detection,metallic surface,tag antenna based sensor
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    Is MO-CMA-ES superior to NSGA-II for the evolution of multi-objective neuro-controllers?

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contributor authorMoshaiov, A. , Abramovich, O.
date accessioned2020-03-12T23:35:18Z
date available2020-03-12T23:35:18Z
date issued2014
identifier other6900433.pdf
identifier urihttp://libsearch.um.ac.ir:80/fum/handle/fum/1117052
formatgeneral
languageEnglish
publisherIEEE
titleIs MO-CMA-ES superior to NSGA-II for the evolution of multi-objective neuro-controllers?
typeConference Paper
contenttypeMetadata Only
identifier padid8286750
subject keywordscrack detection
subject keywordseddy current testing
subject keywordsradiofrequency identification
subject keywordsRFID grids
subject keywordsTABS
subject keywordsUHF band
subject keywordscrack detection
subject keywordshealth monitoring
subject keywordsradiofrequency identification tag antenna-based sensor
subject keywordsrailway track
subject keywordssmart skin
subject keywordsstructural health monitoring
subject keywordsultrahigh frequency band
subject keywordsMetals
subject keywordsMonitoring
subject keywordsRadiofrequency identification
subject keywordsResonant frequency
subject keywordsUHF antennas
subject keywordsNDT&
subject keywordsamp
subject keywordsE
subject keywordsRFID grids
subject keywordscrack detection
subject keywordsmetallic surface
subject keywordstag antenna based sensor
identifier doi10.1109/FENDT.2014.6928296
journal titlevolutionary Computation (CEC), 2014 IEEE Congress on
filesize1670096
citations0
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