A New Classification Method for Stored Grain Insect Infestation Using KIII and SVM Based Electronic Nose

Hdl Handle:
http://hdl.handle.net/10149/550114
Title:
A New Classification Method for Stored Grain Insect Infestation Using KIII and SVM Based Electronic Nose
Authors:
Li, J. (Jie); Xu, D. (Donglai)
Affiliation:
Teesside University. Technology Futures Institute.
Citation:
Li, J., Xu, D. (2014) 'A New Classification Method for Stored Grain Insect Infestation Using KIII and SVM Based Electronic Nose' Advanced Materials Research; 1006-1007:870
Publisher:
Trans Tech Publications
Journal:
Advanced Materials Research
Issue Date:
Aug-2014
URI:
http://hdl.handle.net/10149/550114
DOI:
10.4028/www.scientific.net/AMR.1006-1007.870
Additional Links:
http://www.scientific.net/AMR.1006-1007.870
Type:
Article
Language:
en
ISSN:
1662-8985
Rights:
Author can archive post-print (ie final draft post-refereeing). For full details see http://www.sherpa.ac.uk/romeo [Accessed: 15/04/2015]

Full metadata record

DC FieldValue Language
dc.contributor.authorLi, J. (Jie)en
dc.contributor.authorXu, D. (Donglai)en
dc.date.accessioned2015-04-15T09:10:22Zen
dc.date.available2015-04-15T09:10:22Zen
dc.date.issued2014-08en
dc.identifier.citationAdvanced Materials Research; 1006-1007:870en
dc.identifier.issn1662-8985en
dc.identifier.doi10.4028/www.scientific.net/AMR.1006-1007.870en
dc.identifier.urihttp://hdl.handle.net/10149/550114en
dc.language.isoenen
dc.publisherTrans Tech Publicationsen
dc.relation.urlhttp://www.scientific.net/AMR.1006-1007.870en
dc.rightsAuthor can archive post-print (ie final draft post-refereeing). For full details see http://www.sherpa.ac.uk/romeo [Accessed: 15/04/2015]en
dc.titleA New Classification Method for Stored Grain Insect Infestation Using KIII and SVM Based Electronic Noseen
dc.typeArticleen
dc.contributor.departmentTeesside University. Technology Futures Institute.en
dc.identifier.journalAdvanced Materials Researchen
or.citation.harvardLi, J., Xu, D. (2014) 'A New Classification Method for Stored Grain Insect Infestation Using KIII and SVM Based Electronic Nose' Advanced Materials Research; 1006-1007:870en
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