Forecasting model of short-term traffic flow for road network based on independent component analysis and support vector machine

2009 ◽  
Vol 29 (9) ◽  
pp. 2550-2553 ◽  
Author(s):  
Hong XIE ◽  
Min LIU ◽  
Shu-rong CHEN
Keyword(s):  
Support Vector Machine ◽  
Independent Component Analysis ◽  
Traffic Flow ◽  
Road Network ◽  
Component Analysis ◽  
Independent Component ◽  
Support Vector ◽  
Forecasting Model ◽  
Short Term

Application of Independent Component Analysis in Short-Term Power Forecasting of Wind Farm

2011 ◽  
Vol 63-64 ◽  
pp. 124-128
Author(s):  
Guo Chu Chen ◽  
Peng Wang ◽  
Jin Shou Yu
Keyword(s):  
Support Vector Machine ◽  
Independent Component Analysis ◽  
Least Squares ◽  
Wind Farm ◽  
Absolute Error ◽  
Component Analysis ◽  
Independent Component ◽  
Support Vector ◽  
Number Of Factors ◽  
Power Forecasting

For the difficult problems of measuring and forecasting values interfered by a number of factors, this paper proposed a method of power forecasting based on independent component analysis and least squares support vector machine, and results are modified using the regression. Each independent component from source signals is predicted using least squares support vector machine, the final prediction results obtained by modifying the preliminary predicting power according to the relationship between wind speed and its power. Using the data from a wind farm on the Northeast China wind farm, the simulation results show that this method has higher prediction accuracy, and the mean absolute error from 9.25% down to 5.48%, compared with the simple least squares support vector machine models.

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