Application of least squares vector machines in modelling water vapor and carbon dioxide fluxes over a cropland

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dc.contributor.author Qin, Zhong en_US
dc.contributor.author Yu, Qiang en_US
dc.contributor.author Li, Jun en_US
dc.contributor.author Wu, Zhi-Yi en_US
dc.contributor.author Hu, Bing-Min en_US
dc.contributor.editor en_US
dc.date.accessioned 2010-05-28T09:44:58Z
dc.date.available 2010-05-28T09:44:58Z
dc.date.issued 2005 en_US
dc.identifier 2008006901 en_US
dc.identifier.citation Qin Zhong et al. 2005, 'Application of least squares vector machines in modelling water vapor and carbon dioxide fluxes over a cropland', Zheijiang University Press, vol. 6B, no. 6, pp. 491-495. en_US
dc.identifier.issn 1009-3095 en_US
dc.identifier.other C1UNSUBMIT en_US
dc.identifier.uri http://hdl.handle.net/10453/8709
dc.description.abstract Least squares support vector machines (LS-SVMs), a nonlinear kemel based machine was introduced to investigate the prospects of application of this approach in modelling water vapor and carbon dioxide fluxes above a summer maize field using the dataset obtained in the North China Plain with eddy covariance technique. The performances of the LS-SVMs were compared to the corresponding models obtained with radial basis function (RBF) neural networks. The results indicated the trained LS-SVMs with a radial basis function kernel had satisfactory performance in modelling surface fluxes; its excellent approximation and generalization property shed new light on the study on complex processes in ecosystem. en_US
dc.language en_US
dc.publisher Zheijiang University Press en_US
dc.title Application of least squares vector machines in modelling water vapor and carbon dioxide fluxes over a cropland en_US
dc.parent Journal of Zhejiang University Science en_US
dc.journal.volume 6B en_US
dc.journal.number 6 en_US
dc.publocation China en_US
dc.identifier.startpage 491 en_US
dc.identifier.endpage 495 en_US
dc.cauo.name SCI.Faculty of Science en_US
dc.conference Verified OK en_US
dc.for 100100 en_US
dc.personcode 0000051731 en_US
dc.personcode 107001 en_US
dc.personcode 0000071175 en_US
dc.personcode 0000052150 en_US
dc.personcode 0000052128 en_US
dc.percentage 100 en_US
dc.classification.name Agricultural Biotechnology en_US
dc.classification.type FOR-08 en_US
dc.edition en_US
dc.custom en_US
dc.date.activity en_US
dc.location.activity en_US
dc.description.keywords Least squares support vector machines (LS-SVMs), Water vapor and carbon dioxide fluxes exchange, Radial basis function (RBF) neural networks en_US
dc.staffid en_US


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