Robust Total Least Square Algorithm Of Probability-integral Method Prediction Parameters

The exploitation of mineral resources will cause certain damage to the rock mass surrounding the mining area.According to the physical properties of rock mass and the influence of the earth's gravity,the rock mass and surface will produce continuous movement,deformation and discontinuous damage(cracking,caving,etc.).In the actual production of the mining area,in order to obtain the relevant parameters of subsidence and surface movement,prior to mining,an appropriate prediction function is selected based on the geological mining conditions and the mining level of the mining area.Calculate the impact of the damage caused by mining on the surface in advance,respond to changes in time,and then formulate a scientific and reasonable plan to guide the production of the mine area.Probabilistic Integral Method is used to predict movement and deformation during production in most mining areas.However,the coefficient matrix of the function model of the probability integral method is actually composed of observations,and the inevitable error of the observations causes errors in the coefficient matrix.Therefore,we need to consider the error of the coefficient matrix when we calculate the prediction parameters.At the same time,some of the observations will be mixed with some gross errors or different values.When using the least squares method to obtain the prediction parameters,the predicted results are easily distorted due to the effects of different values and gross errors.In view of the two situations mentioned above,this paper proposes the method of total least squares robust algorithm under the probabilistic integral curve fitting model.The main contents and results of the study are as follows:1.Study the basic principles and solving methods of Least Squares,Total Least Squares,and Robust Total Least Squares.The analysis of the example shows that the total least squares robust algorithm can effectively solve the problem of the error of the coefficient matrix and the presence of gross errors in the observed values.2.Analyze the practicality of the total least squares robust algorithm in actual surveying and mapping work and the feasibility of using this algorithm to calculate the expected parameters of the probability.integral method.By introducing the basic principle of the probability integration method,the mathematical model and the stochastic model for calculating the prediction parameters of the probability integration method using the above three algorithms are obtained.3.Based on the measured data of the 1222(1)working face of Zhujidong Coal Mine,this paper uses the least square method,the total least squares method and the total least squares robust algorithm to obtain the prediction parameters and the evaluation of the fitting accuracy.The results show that the prediction parameters obtained by the total least squares robust algorithm are more consistent with the variation of measured subsidence,and the accuracy is the highest.