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It is significant that to get accurate prediction of dynamic traffic flow for intelligent traffic system management and control. A traffic flow prediction model of spatial-temporal 2D (2-dimension) data fusing based on SVM (Support Vector Machines) is put forward in this paper. The section flow results predicted by temporal SVM, spatial SVM and spatial-temporal 2D data fusing are all satisfied the...
During gene expression, transcription factors are unable to bind to a transcription binding site (TFBS) involved in regulation if DNA methylation has occurred at the TFBS. Methyl-CpG-binding proteins may also occupy the TFBS and prevent the functioning of a transcription factor. Thus, the methylation status of CpG sites is an important issue when trying to understand gene regulation and shows strong...
In this paper we apply the nonlinear time series prediction method to the traffic measurements data. Based on the phase space reconstruction, the support vector machine prediction method is used to predict the traffic measurements data, and the neighbor point selection method is used to choose the number of nearest neighbor points for the support vector machine regression model. The experiment results...
Alumina powder flow in electrolytic aluminum plant for the production of alumina can not be precise measured online, the Least Squares Support Vector Machines (LS -SVM) was applied in the modeling of alumina powder flow estimation in the process of alumina conveying in this paper, and the soft sensor model based on LS - SVM was compared with the soft sensor model based on RBF. The result of simulation...
In this study, a dynamic model based on least squares support vector machines is proposed to forecast the daily peak loads of a month. The model function is got from the training data set using least squares support vector machines. In the time series prediction process, new data points are included into training data set and some of the old ones are deleted, so as to track the dynamics of the nonlinear...
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