Title :
Application of Support Vector Machines in the prediction of broken zone in surrounding rock
Author :
Guo, Wei ; Jiang, Deyi ; Liu, Chun
Author_Institution :
Key Lab. for the Exploitation of Southwestern, Chongqing Univ., Chongqing, China
Abstract :
Introduce the principles of Support Vector Machines, and indicate the broken zone thickness can be forecasted by four factors: rock strength, joint coefficient, buried depth and span length. The results show that Support Vector Machine (SVM) is a reliable method to predict broken zone thickness, and the predictive values agree well with the verify data.
Keywords :
geophysical techniques; rocks; support vector machines; broken zone thickness; buried depth; joint coefficient; rock strength; span length; support vector machine; Joints; Kernel; Mathematical model; Rocks; Stress; Support vector machines; Training; broken zone; prediction; support vector machines;
Conference_Titel :
Remote Sensing, Environment and Transportation Engineering (RSETE), 2011 International Conference on
Conference_Location :
Nanjing
Print_ISBN :
978-1-4244-9172-8
DOI :
10.1109/RSETE.2011.5964228
