Dissertation
Dissertation > SCIENCE AND > Journal of Systems Science > Systems,modern systems theory > Gray system theory

The Establishment and Application of Combination Forecasting Model

Author LiuSuBing
Tutor WangQiuPing
School Xi'an University of Technology
Course Applied Mathematics
Keywords Combination model Grey Forecasting Grey Relational Analysis ARMA model Neural Network Model
CLC N941.5
Type Master's thesis
Year 2008
Downloads 615
Quotes 16
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With the new theory of gray system theory , BP neural network technology used to predict the field of forecasting techniques has been a great development . Strong fusion and penetration of gray prediction model with a general prediction model , the combination of gray model with other models for analysis and forecasting can improve the prediction accuracy . Therefore, analysis and research on the combination of gray model with other models , combination forecasting model and forecast China's energy consumption . The main contents of this paper and the results are as follows : 1 . Combination of ARMA model based on gray prediction GM (1,1) model , triangular model and time series analysis predict touch -type TGMA ( 1,1 ) . In this model, gray forecasting GM (1,1) model fits the data sequence trend term , residual series of triangular and ARMA models capture system . Building a gray neural network combined forecasting model . The combination of improved BP neural network of the three gray prediction model ( gray prediction model of optimal prediction model GOM (1,1), unbiased gray prediction model , improved metabolism ) . Gray neural network combined forecasting model to make further improvements . Gray relational analysis of several factors to identify a greater impact on China's energy consumption , to them time series data as the input of BP neural network , such a comprehensive and integrated manner taking into account the impact factors of the energy consumption of the system , thereby increasing the prediction accuracy.

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