ON MODEL COMBINED FORECASTING OF TEMPORAL DATA BASED ON PURSUIT PROJECTION LEARNING NETWORK
Yan Yong 1) ; Yang Bisheng 2) ;and Wang Ying 1)
1)Department of Spatial Information and Surveying and Mapping, University of Science and Technology of Suzhou, Suzhou 2150112)State Key Laboratory for Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University,Wuhan 430079
Abstract：Aiming at observed time series data, a new forecast model which has the advantages of combination prediction and Pursuit Projection Learning Network(PPLN) is put forward. The model uses several static forecasting models to obtain the tendency part and uses the regression model for periodic part, then takes them as input signals of PPLN, calculates the weights between the models by PPLN which has the ability to approximate the complex nonlinear function. The model resolves a difficult problem of combination prediction.The experimental results show that new forecast model has a higher accuracy than traditional curvefitting or combination forecasting method with variable weight, can be applied to other data prediction problems in the subject of surveying and mapping.
Yan Yong ,Yang Bisheng ,and Wang Ying . ON MODEL COMBINED FORECASTING OF TEMPORAL DATA BASED ON PURSUIT PROJECTION LEARNING NETWORK[J]. jgg, 2010, 30(第3期): 105-109.
