DocumentCode
2835286
Title
A New Kind of Optimized Method of Grey Prediction Model and Its Applications in Deformation
Author
Gao, Cai-yun ; Gao, Ning
Author_Institution
Dept. of Survey & Urban Spatial Inf., Henan Univ. of Urban Constr., Pingdingshan, China
fYear
2009
fDate
19-20 Dec. 2009
Firstpage
1
Lastpage
4
Abstract
Accurately estimating the deformation of rock mass is a very important work for surveyors. Aiming at the limitation of the conventional grey GM (1, 1) model, we propose that the structure methods of background value and the initial condition in grey GM(1, 1) model have an important influence on this model´s precision and adaptableility. From this point of view, an optimized grey model is developed. Firstly, the structure method of background value is obtained by using integrated calculating formula of background value. The new calculating formula of background value gives GM (1, 1) model the ability to optimize the modeling results. Then according to the new rest first principle of the grey model, the nth component of X (1) is supposed to be the initial condition of the pessimistic differential model. By using the optimized model to analyze and predict the deformation of rock mass and comparing this optimized model with other models, we finally draw a conclusion that this optimized model is able to improve the precision of prediction and therefore can be applied to deformation data analysis.
Keywords
deformation; grey systems; initial value problems; background value; deformation data analysis; grey prediction model; pessimistic differential model; rock mass deformation; surveying work; Data analysis; Data processing; Decision making; Deformable models; Economic forecasting; Equations; Mathematical model; Monitoring; Optimization methods; Predictive models;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Engineering and Computer Science, 2009. ICIECS 2009. International Conference on
Conference_Location
Wuhan
Print_ISBN
978-1-4244-4994-1
Type
conf
DOI
10.1109/ICIECS.2009.5364387
Filename
5364387
Link To Document