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Conference Paper: Route selection for vehicle navigation and control

TitleRoute selection for vehicle navigation and control
Authors
Issue Date2007
PublisherInstitute of Electrical and Electronics Engineers. The Journal's web site is located at http://www.ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1001443
Citation
The 5th IEEE International Conference on Industrial Informatics (INDIN 2007), Vienna, Austria, 23-27 July 2007. In IEEE International Conference on Industrial Informatics, 2007 v. 2, p. 693-698 How to Cite?
AbstractThis paper presents an application of neural-fuzzy methodology for the problem of route selection in a typical vehicle navigation and control system. The idea of the primary attributes of a route is discussed, and a neural-fuzzy system is developed to help a user to select a route out of the many possible routes from an origin to the destination. The user may not adopt the recommendation provided by the system and choose an alternate route. One novel feature of the system is that the neural-fuzzy system can adapt itself by changing the weights of the defined fuzzy rules through a training procedure. Two examples are given in this paper to illustrate how the route selection/ranking system can be made adaptive to the past choice or preference of the user. © 2007 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/158493
ISBN
ISSN
2020 SCImago Journal Rankings: 0.195
References

 

DC FieldValueLanguage
dc.contributor.authorPang, Gen_US
dc.contributor.authorChu, MHen_US
dc.date.accessioned2012-08-08T08:59:55Z-
dc.date.available2012-08-08T08:59:55Z-
dc.date.issued2007en_US
dc.identifier.citationThe 5th IEEE International Conference on Industrial Informatics (INDIN 2007), Vienna, Austria, 23-27 July 2007. In IEEE International Conference on Industrial Informatics, 2007 v. 2, p. 693-698en_US
dc.identifier.isbn1-4244-0865-2-
dc.identifier.issn1935-4576en_US
dc.identifier.urihttp://hdl.handle.net/10722/158493-
dc.description.abstractThis paper presents an application of neural-fuzzy methodology for the problem of route selection in a typical vehicle navigation and control system. The idea of the primary attributes of a route is discussed, and a neural-fuzzy system is developed to help a user to select a route out of the many possible routes from an origin to the destination. The user may not adopt the recommendation provided by the system and choose an alternate route. One novel feature of the system is that the neural-fuzzy system can adapt itself by changing the weights of the defined fuzzy rules through a training procedure. Two examples are given in this paper to illustrate how the route selection/ranking system can be made adaptive to the past choice or preference of the user. © 2007 IEEE.en_US
dc.languageengen_US
dc.publisherInstitute of Electrical and Electronics Engineers. The Journal's web site is located at http://www.ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1001443-
dc.relation.ispartofIEEE International Conference on Industrial Informaticsen_US
dc.rights©2007 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.-
dc.titleRoute selection for vehicle navigation and controlen_US
dc.typeConference_Paperen_US
dc.identifier.emailPang, G: gpang@eee.hku.hken_US
dc.identifier.emailChu, MH: mhchu@eee.hku.hk-
dc.identifier.authorityPang, G=rp00162en_US
dc.description.naturepublished_or_final_versionen_US
dc.identifier.doi10.1109/INDIN.2007.4384857en_US
dc.identifier.scopuseid_2-s2.0-39749139514en_US
dc.identifier.hkuros143910-
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-39749139514&selection=ref&src=s&origin=recordpageen_US
dc.identifier.volume2en_US
dc.identifier.spage693en_US
dc.identifier.epage698en_US
dc.publisher.placeUnited Statesen_US
dc.identifier.scopusauthoridChu, MH=47461010000en_US
dc.identifier.scopusauthoridPang, G=7103393283en_US
dc.customcontrol.immutablesml 140819-
dc.identifier.issnl1935-4576-

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