DocumentCode :
3172107
Title :
Research on Support vector machine prediction on surrounding rock deformation based on fuzzy information granulation
Author :
Qiao, Lan ; Liang, Shuang ; Cui, Fang
Author_Institution :
State Key Lab. of High-Efficient Min. & Safety of Metal Mines, Univ. of Sci. & Technol. Beijing, Beijing, China
fYear :
2011
fDate :
16-18 April 2011
Firstpage :
3466
Lastpage :
3469
Abstract :
On the basis of our realization to the world, granulation is one of the basis concepts. It refers to the whole divides into the parts. Information granulation has a key role in many methods and technical domains. The theory of fuzzy information granulation (TFIG) is elicited by man´s information granulation method and based this to infer. Support vector machine (SVM) is an effective method to predict the time series. This article studies the prediction of surrounding rock deformation by using SVM method based on TFIG. Combining with a project case, the algorithm is realized by Matlab program. The results show that this new method can well and truly predict the bound of the next five day´s displacement of surrounding rock.
Keywords :
deformation; fuzzy set theory; geophysics computing; rocks; support vector machines; time series; Matlab program; SVM; TFIG; support vector machine prediction; surrounding rock deformation prediction; theory of fuzzy information granulation; time series; Conferences; Metals; Prediction algorithms; Rocks; Rough sets; Support vector machines; Time series analysis; SVM; deformation prediction; fuzzy information granulation; surrounding rock;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Consumer Electronics, Communications and Networks (CECNet), 2011 International Conference on
Conference_Location :
XianNing
Print_ISBN :
978-1-61284-458-9
Type :
conf
DOI :
10.1109/CECNET.2011.5769451
Filename :
5769451
Link To Document :
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