2016 The 4th International Conference on Geology Resource Management and Sustainable Development (ICGRMSD 2016)

79 / 2015-10-27 16:17:45

Application of Displacement Back Analysis by GA-NN in Inclined Shaft under Influence of Mining Field

displacement back analysis,genetic analysis,artificial neural network,936

It is important to estimate exactly the stability of development opening due to the changing of coal mining face. This paper suggested a kind of GA-NN displacement back analysis in order to determine mechanical properties and in-situ stress of rock mass surrounding development inclined shaft under influence of mining field. At first, training data set of ANN based on the orthogonal table and FLAC3D. Then, Back analysis parameters are established as Elastic modulus (E) and Cohesion (C), Internal friction angle () of rock mass, lateral stress factor (), and nonlinear relation between convergence displacements and those is obtained by using BP ANN. Secondly, optimal parameters are determined by genetic algorithm using the openings convergence displacements measured in situ. Here, the openings convergence displacements mean the stable displacements, which are estimated with Grey Model (GM). Relative error between convergence displacements from numerical analysis with back analysis parameters and measured one in situ was less than 3%. Thus, the displacement back analysis based on GA-NN can be applied to stability estimation of openings.