Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/22757
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dc.contributor.advisor-
dc.contributor.authorYang, Q-
dc.contributor.authorLai, LL-
dc.contributor.authorLai, CS-
dc.date.accessioned2021-05-24T12:27:57Z-
dc.date.available2013-01-01-
dc.date.available2021-05-24T12:27:57Z-
dc.date.issued2014-
dc.identifier.citationProceedings - International Conference on Machine Learning and Cybernetics, 2013, 1 pp. 104 - 107en_US
dc.identifier.isbn9781479902576-
dc.identifier.issn2160-133X-
dc.identifier.issn2160-1348-
dc.identifier.urihttp://bura.brunel.ac.uk/handle/2438/22757-
dc.description.abstractThis paper studies the cost benefit analysis (CBA) methods that can improve the decision support capability of smart grid deployment. Critical review based on various methodologies adopted worldwide has been carried out and detailed analysis was conducted. The finding demonstrates as there are no agreed guidelines for CBA. Also in real-life situation, due to large amount of data and data quality could be low, it is suggested developing CBA methodology based upon intelligent techniques such as neural and evolutionary computing may have a good potential for the future.en_US
dc.format.extent104 - 107-
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.rights© 2013 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.              -
dc.subjectCost-benefit Analysisen_US
dc.subjectSmart Griden_US
dc.subjectDecision Supporten_US
dc.titleMethodology for cost benefit analysis of smart grid used in decision supporten_US
dc.typeConference Paperen_US
dc.identifier.doihttp://dx.doi.org/10.1109/ICMLC.2013.6890452-
dc.relation.isPartOfProceedings - International Conference on Machine Learning and Cybernetics-
pubs.publication-statusPublished-
pubs.volume1-
dc.identifier.eissn2160-1348-
Appears in Collections:Dept of Electronic and Electrical Engineering Research Papers

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