DocumentCode :
1801300
Title :
Based on simpson formula improved non-interval GM(1,1) model and application
Author :
Wu Fu-fei ; Shi Ke-bin ; Yiziteliopu, Nuerkaili ; Dong Shuang-kuai
Author_Institution :
Coll. of Civil & Hydraulic Eng., Xin jiang Agric. Univ., Urumqi, China
fYear :
2013
fDate :
26-28 July 2013
Firstpage :
8431
Lastpage :
8435
Abstract :
Non-interval gray GM (1,1) model is a tradition from the GM (1,1) model ranging parameters. Traditional unequal interval gray GM (1,1) model prediction accuracy is lower, in order to improve the unequal interval gray GM (1,1) model prediction accuracy, through the establishment of gray model based on the new rates, and analyze the background value sources of error; then using Simpson formula to improve the background value, By predicting that: non-interval improved gray GM (1,1) model accuracy is higher and apply to a summation was the number of regular sequence; their average error is less than 0.1%, compared with the traditional interval gray GM (1,1) model 0.35%; the over fitting polynomial 4.23%. Therefore, the unequal interval gray GM (1,1) model can be improved to meet the accuracy requirements of the higher forecast instances.
Keywords :
forecasting theory; grey systems; GM(1,1) model prediction accuracy; GM(1,1) model ranging parameters; Simpson formula; background value; forecast instance; improved noninterval gray GM(1,1) model; overfitting polynomial; Accuracy; Analytical models; Chemical engineering; Distance measurement; Educational institutions; Fitting; Predictive models; Simpson formula; background values; improve; non-interval;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control Conference (CCC), 2013 32nd Chinese
Conference_Location :
Xi´an
Type :
conf
Filename :
6640932
Link To Document :
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