The Study Of Mine Geological Environment Evaluation Method In Fujian,China

With the continuous development and utilization of mineral resources,the corresponding mine environmental problems also arise.The evaluation results of the mine geological environment problems in serious area can provide the basis for the mine management and planning of the related departments,and provide support for the sustainable economic development and the green mine construction.Many researchers have studied the evaluation of mine geological environment,and there are still many difficulties affecting the evaluation results.The selection of evaluation factors is relatively simple,which can't fully reflect the mine geological environment in the study area;The quantitative criteria of the evaluation factors are inconsistent,which leads to the diversification of the evaluation results in the same area;The uncertainty of the evaluation scale leads to the inaccuracy of the evaluation results;The evaluation method used is unreasonable,which will reduce the computation efficiency and the accuracy of evaluation.Taking Fujian as the study area,this paper uses the human-computer interaction interpretation,object oriented information extraction and other remote sensing and GIS technology to extract the information of natural geography,basic geology,resource damage and mine environment,and establish the system of mine geological environment rating factor.On this basis,the multi-scale mine geological environment evaluation is carried out in the study area,and the optimal evaluation scale of the study area is selected by analyzing and evaluating the scale effect.The quantum particle swarm optimization(QPSO)is used to optimize the parameters of the least squaressupport vector machine(LS-SVM),and the improved algorithm(QPSO-LS-SVM)is used to evaluate the geological environment of the mining area.Compared with BP neural network and FCE-AHP method,the best evaluation method is selected.The main achievements of this paper are as follows:(1)Through reading and summarizing a large number of documents and referring to the selection criteria of the evaluation factors of mine geological environment at home and abroad,the mine geological environment rating factor of the study area is determined,which can reflect the mine geological environment in the study area more comprehensively.(2)Through the evaluation of mine geological environment under different scales in the study area,the best evaluation criteria for the study area have been identified.(3)In this paper,the least squares-support vector machine(LS-SVM)is introduced as an evaluation method.On the basis of LS-SVM algorithm,an improved QPSO algorithm is proposed to optimize the parameters of LS-SVM,eliminate the randomness of artificial selection of parameters,and greatly shorten the time of training samples.(4)Through the comparison and analysis of the evaluation results of the three evaluation methods of QPSO-LS-SVM,BP neural network and FCE-AHP,it is found that the evaluation results of QPSO-LS-SVM are more rapid and more in line with the actual situation of the study area.