Study of the method to calculate subsidence coefficient based on svm.pdf

Procedia Earth and Planetary Science Procedia Earth and Planetary Science 1 (2009) 970–976 /locate/procedia The 6th International Conference on Mining Science Technology Study of the method to calculate subsidence coefficient based on SVM Tan Zhi-xianga,b,*, Li Pei-xiana,b, Yan Li-lia,b, Deng Ka-zhonga,b aKey Laboratory of Resources and Environment Information Engineering in Jiangsu Province, Xuzhou 221008, China bSchool of Environmental Science and Spatial Information, China University of Mining Technology, Xuzhou 221008, China Abstract Subsidence coefficient is a key parameter for ground movement and deformation prediction when mining under the building, water, and railway; so how to get exact subsidence coefficient is one of the most important problems in the discipline of mining subsidence. Support vector machine (SVM) is a new algorithm of machine learning based on statistical learning theory. Compared with traditional method, SVM can be established under condition of deficient samples and abnormal observation result can be rejected effectively. Based on comprehensive analysis of effect factors on subsidence coefficient such as mechanical characteristics of upper rock stratum, thickness of alluvium deposit, ratio value of mining deepness to thic