Genetic Programming Model For Prediction Of Rockmass Movement Due To Underground Mining And It's Engineering Application

The newly optimization method of genetic programming to estimate the rockmass movement parameters and the max surface subsidence due to underground mining is given in this dissertation. And the theorical models are established and used for estimating the rockmass movement parameters and the max surface subsidence. This text has discussed the essential feature of the mathematical model for predicting rockmass movement under flatlands and mountainous areas. Also, genetic programming models are set up to estimate corresponding parameters, that is, a large of practical data of mining induced surface subsidence are used to train genetic programming model and then genetic programming models of the subsidence coefficient, the tangent of major influence angle, horizontal movement coefficient and the max surface subsidence are eatablished. Finally, the nonlinear relationship between the aboved parameters and their influenced factors are obtained, the expression formula of basic functions are provided. Therefore, it offers a artificial method for rockmass movement prediction. In addition, Matlab language whose visual degree to be quite high is used to output a large number of 2D and 3D figures, making the results clearly, so it is benefit application in. engineering. Utilizing the article's model to estimate the rockmass movement parameters and the max surface subsidence of three underground mines, theorical results are compared with the survey results, the errors are small. In sum, this text's model gets rid of human factor in parameters estimating totally, the precision of the output can meet engineering need, so this method is worth popularation and application in this domain.