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Time series analysis is to explain correlation and the main features of the data in chronological order by using appropriate statistical models. Since the past electricity generated sequence in China shows a strong seasonal variations and several values for January are lost in recent years, estimating the missing values is an important task before building a model. This paper will estimate the missing...
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...
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...
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