Show simple item record

dc.contributor.authorSusanto, Ferry
dc.contributor.authorBudi, Setia
dc.contributor.authorde Souza, Paulo
dc.contributor.authorEngelke, Ulrich
dc.contributor.authorHe, Jing
dc.date.accessioned2021-12-08T06:38:52Z
dc.date.available2021-12-08T06:38:52Z
dc.date.issued2016
dc.identifier.issn1545-598Xen_US
dc.identifier.doi10.1109/LGRS.2016.2525980en_US
dc.identifier.urihttp://hdl.handle.net/10072/409713
dc.description.abstractAn evolutionary algorithm (EA)-assisted spatial sampling methodology is proposed to assist decision makers in sensor network (SN) deployments. We incorporated an interpolation technique with leave-one-out cross-validation (LOOCV) to assess the representativeness of a particular SN design. For the validation of our method, we utilized Tasmania's South Esk Hydrological Model developed by the Commonwealth Scientific and Industrial Research Organisation, which includes a range of environmental variables describing the landscape. We demonstrated that our proposed methodology is capable of assisting in the initial design of SN deployment. Ordinary Kriging is shown to be the best suited spatial interpolation algorithm for the EA's LOOCV under the current empirical study.en_US
dc.description.peerreviewedYesen_US
dc.languageEnglishen_US
dc.publisherIEEEen_US
dc.relation.ispartofpagefrom575en_US
dc.relation.ispartofpageto579en_US
dc.relation.ispartofissue4en_US
dc.relation.ispartofjournalIEEE Geoscience and Remote Sensing Lettersen_US
dc.relation.ispartofvolume13en_US
dc.subject.fieldofresearchArtificial intelligenceen_US
dc.subject.fieldofresearchElectronics, sensors and digital hardwareen_US
dc.subject.fieldofresearchGeomatic engineeringen_US
dc.subject.fieldofresearchcode4602en_US
dc.subject.fieldofresearchcode4009en_US
dc.subject.fieldofresearchcode4013en_US
dc.subject.keywordsScience & Technologyen_US
dc.subject.keywordsPhysical Sciencesen_US
dc.subject.keywordsTechnologyen_US
dc.subject.keywordsGeochemistry & Geophysicsen_US
dc.subject.keywordsEngineering, Electrical & Electronicen_US
dc.titleDesign of environmental sensor networks using evolutionary algorithmsen_US
dc.typeJournal articleen_US
dc.type.descriptionC1 - Articlesen_US
dcterms.bibliographicCitationSusanto, F; Budi, S; de Souza, P; Engelke, U; He, J, Design of environmental sensor networks using evolutionary algorithms, IEEE Geoscience and Remote Sensing Letters, 2016, 13 (4), pp. 575-579en_US
dc.date.updated2021-11-03T04:34:01Z
dc.description.versionAccepted Manuscript (AM)en_US
gro.rights.copyright© 2016 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.en_US
gro.hasfulltextFull Text
gro.griffith.authorDe Souza Junior, Paulo A.


Files in this item

This item appears in the following Collection(s)

  • Journal articles
    Contains articles published by Griffith authors in scholarly journals.

Show simple item record