Study of probability integration method parameter inversion by the genetic algorithm

Li Peixian; Peng Di; Tan Zhixiang; Deng Kazhong

首页> 外文期刊>矿业科学技术学报：英文版 >Study of probability integration method parameter inversion by the genetic algorithm

【24h】

Study of probability integration method parameter inversion by the genetic algorithm

机译：遗传算法的概率积分法参数反演研究

获取原文

获取原文并翻译 | 示例

掌桥外文数据库（机构版） >>

开具论文收录证明 >>

文献代查 >>

页面导航

摘要
著录项
相关主题

摘要

In order to obtain accurate probability integration method (PIM) parameters for surface movement of multi-panel mining, a genetic algorithm (GA) was used to optimize the parameters. As the measured surface movement is affected by more than one mining panel, traditional PIM parameter inversion model is difficult to ensure the reliability of the results due to the complexity of rock movement. With crossover, mutation and selection operators, GA can perform a global optimization search and has high computation efficiency. Compared with the pattern search algorithm, the fitness function can avoid falling into local minima traps. GA reduces the risk of local minima traps which improves the accuracy and reliability with the mutation mechanism. Application at Xuehu colliery shows that GA can be used to inverse the PIM parameters for multi-panel surface movement observation, and reliable results can be obtained. The research provides a new way for back-analysis of PIM parameters for mining subsidence under complex conditions.

机译：为了获得用于多面板采矿的地表运动的准确概率积分方法（PIM）参数，使用遗传算法（GA）来优化参数。由于测量的地表运动受一个以上采矿面板的影响，由于岩石运动的复杂性，传统的PIM参数反演模型难以确保结果的可靠性。借助交叉，变异和选择运算符，GA可以执行全局优化搜索并具有很高的计算效率。与模式搜索算法相比，适应度函数可以避免陷入局部最小值陷阱。 GA降低了局部极小陷阱的风险，从而通过突变机制提高了准确性和可靠性。在雪湖煤矿的应用表明，遗传算法可用于多面板表面运动观测的PIM参数反演，并可获得可靠的结果。该研究为复杂条件下开采沉陷的PIM参数反分析提供了新途径。

著录项

来源
《矿业科学技术学报：英文版》 |2017年第006期|P.1073-1079|共7页
作者
Li Peixian; Peng Di; Tan Zhixiang; Deng Kazhong;
展开▼
作者单位

[1]College of Geoscience and Surveying Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China;

[1]College of Geoscience and Surveying Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China;

[2]School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China;

[2]School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China;

展开▼
收录信息中国科学引文数据库(CSCD);
原文格式 PDF
正文语种 CHI
中图分类矿业工程;
关键词
Probability integration method; GA; Mining subsidence; Parameter inversion; Multiobjective optimization;

机译：概率积分法;遗传算法;开采沉陷;参数反演;多目标优化;

Study of probability integration method parameter inversion by the genetic algorithm

摘要

著录项

相关主题

期刊订阅