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 s...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.展开更多
Supercritical water oxidation （SCWO） is an effective method for wastewater treatment. In this study, a lot of experiments are carried out to study the influence of various factors on the aniline destruction rate in ...Supercritical water oxidation （SCWO） is an effective method for wastewater treatment. In this study, a lot of experiments are carried out to study the influence of various factors on the aniline destruction rate in the SCWO process with a novel experiment setup. The experimental results show that the aniline destruction rate rises with the increase of the residence time, the reaction temperature and the reaction pressure. A dynamics analysis of the aniline SCWO reaction is conducted and the dynamic equation is obtained.展开更多
基金Project supported by the National Science Fund for OutstandingYouth Overseas (No. 40328001) and the Key Research Plan of theKnowledge Innovation Project of the Institute of Geographic Sciencesand Natural Resources, Chinese Academy of Sciences (No.KZCXI-SW-01)
文摘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.
文摘Supercritical water oxidation （SCWO） is an effective method for wastewater treatment. In this study, a lot of experiments are carried out to study the influence of various factors on the aniline destruction rate in the SCWO process with a novel experiment setup. The experimental results show that the aniline destruction rate rises with the increase of the residence time, the reaction temperature and the reaction pressure. A dynamics analysis of the aniline SCWO reaction is conducted and the dynamic equation is obtained.
