Application of SVM Combined with Mackov Chain for Inventory Prediction in Supply Chain

UTSePress Research/Manakin Repository

Search UTSePress Research


Advanced Search

Browse

My Account

Show simple item record

dc.contributor.author Wang, Jianzhou en_US
dc.contributor.author Zhu, Wenjin en_US
dc.contributor.author Sun, Donghuai en_US
dc.contributor.author Lu, Hai Yan (Helen) en_US
dc.contributor.editor T. Hou and S. Mendlinger en_US
dc.date.accessioned 2010-05-28T10:00:48Z
dc.date.available 2010-05-28T10:00:48Z
dc.date.issued 2008 en_US
dc.identifier 2008001841 en_US
dc.identifier.citation Wang Jianzhou et al. 2008, 'Application of SVM Combined with Mackov Chain for Inventory Prediction in Supply Chain', IEEE, Piscataway, USA, pp. 1-4. en_US
dc.identifier.issn 978-1-4244-2107-7 en_US
dc.identifier.other E1UNSUBMIT en_US
dc.identifier.uri http://hdl.handle.net/10453/10957
dc.description.abstract The aim of this paper is to predict the inventory of the relevant upstream enterprises in supply chain. The support vector machine, a novel artificial intelligence-based method developed from statistical learning theory, is adopted herein to establish a short-term stage forecasting model. However, take the fact into account that demand signal is affected by variant random factors and behaves big uncertainty, the predicted accuracy of SVM is not approving when the data show great randomness. It is obligatory that we present Markov chain to improve the predicted accuracy of SVM. This combined model takes advantage of the high predictable power of SVM model and at the same time take advantage of the prediction power of Markov chain modeling on the discrete states based on the SVM modeling residual sequence. Then we use the statistical data of the output of the gasoline of China from Feb-06 to Dec-07 for a validation of the effectiveness of the above model. en_US
dc.language en_US
dc.publisher IEEE en_US
dc.relation.isbasedon http://dx.doi.org/10.1109/WiCom.2008.1543 en_US
dc.title Application of SVM Combined with Mackov Chain for Inventory Prediction in Supply Chain en_US
dc.parent Proceedings of the 4th International Conference on Wireless Communications, Networking, and Mobile Computing en_US
dc.journal.volume en_US
dc.journal.number en_US
dc.publocation Piscataway, USA en_US
dc.identifier.startpage 1 en_US
dc.identifier.endpage 4 en_US
dc.cauo.name FEIT.School of Software en_US
dc.conference Verified OK en_US
dc.for 080100 en_US
dc.personcode 0000047860 en_US
dc.personcode 0000047858 en_US
dc.personcode 0000047859 en_US
dc.personcode 000516 en_US
dc.percentage 100 en_US
dc.classification.name Distributed Computing en_US
dc.classification.type FOR-08 en_US
dc.edition en_US
dc.custom International Conference on Wireless Communications, Networking and Mobile Computing en_US
dc.date.activity 20081012 en_US
dc.location.activity Dalian, China en_US
dc.description.keywords SVM, supply chain, Markov chain, predict en_US
dc.staffid en_US
dc.staffid 000516 en_US


Files in this item

This item appears in the following Collection(s)

Show simple item record