DocumentCode :
2459332
Title :
Prediction analysis of destroyed coalseam floor depth based on v-SVR algorithm
Author :
Jiang, Chunlu ; Sun, Qiang ; Jiang, Zhenquan ; Zhu, Shuyun
Author_Institution :
Sch. of Resource & Earth Sci., China Univ. of Min. & Technol., Xuzhou, China
fYear :
2011
fDate :
24-26 June 2011
Firstpage :
4264
Lastpage :
4267
Abstract :
There are main six factors controlling failure zone floor depth including mining depth, coal seam inclination angle, mining thickness, workface inclined length, coal floor anti-destructive capacity, fault or fracture zone. Inorder to prediet failure depth of coal seam floor, based on the analysis of the factors influencing the failure depth of coal seam floor, a model to predict the failure depth is established by applying the theory of v-SVR algorithm. A large amount of on-site observed data was used as learning and training samples. Optimized the parameters of the model by grid-search method and tested the model performance. The model considered comprehensive affected factors and considered the nonlinear relationship between factors and target value.The results show that v-SVR algorithm model predictive value is more closer to measured datas compared to empirical formula calculated value.
Keywords :
coal; failure (mechanical); fracture; learning (artificial intelligence); mechanical engineering computing; mining; regression analysis; search problems; support vector machines; coal floor antidestructive capacity; coal seam inclination angle; destroyed coalseam floor depth; failure zone floor depth; fault zone; fracture zone; grid search method; learning samples; mining depth; mining thickness; prediction analysis; training samples; v-SVR algorithm; workface inclined length; Algorithm design and analysis; Coal; Educational institutions; Floors; Geoscience; Prediction algorithms; Support vector machines; coal mining over confined aquifer; destroyed floor depth; grid-search method; v-SVR;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Remote Sensing, Environment and Transportation Engineering (RSETE), 2011 International Conference on
Conference_Location :
Nanjing
Print_ISBN :
978-1-4244-9172-8
Type :
conf
DOI :
10.1109/RSETE.2011.5965272
Filename :
5965272
Link To Document :
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