【摘要】 以预测煤矿开采而引起的地表高程的损失为目的,通过灰色系统理论的建模、关联度分析和残差辨识,建立基于贫信息的传统GM(1,1)模型、GM(1,1)残差模型、时序残差GM(1,1)模型,又建立基于原始数据具有绝对误差的灰色CompertzⅠ和灰色LogisticⅠ模型与具有相对误差的灰色CompertzⅡ和灰色LogisticⅡ模型,并将其应用到金竹山矿业公司土珠煤矿的地表沉降量的实际预测分析中,对该矿2007年度1—10月的地表高程损失量进行灰色生成后,建立了7种灰色预测模型。根据其预测值的精度检验结果对比分析表明,所建立的7种模型均为一级(好)模型,且灰色CompertzIⅡ和灰色LogisticIⅡ模型远优于传统GM(1,1)模型,预测精度高,可靠性强,对煤矿开采的复垦规划有重要指导作用。更多还原

【Abstract】 For the purpose of predicting the loss of surface elevation caused by coal mining, the traditional poor-information-based GM(1,1) model, GM(1,1) residual model and timing residual GM(1,1) model were set up according to grey system modeling, correlation analysis and residual recognition. Meanwhile, the original-data-based grey CompertzI model with absolute error, the grey LogisticI model, and the grey CompertzII model and grey LogisticII model that both have relative error were also set up. Then, these models were applied to the actual prediction analysis of subsidence value in Tuzhu Coal Mine of Jinzhushan Mining Company. After a grey generation was made on the loss of surface elevation from January to October in 2007, seven grey prediction models were set up. Comparative analysis on the accuracy test of these prediction values gained by these grey models shows that the seven models are all firs-level (good) models, and that the grey CompertzII model and grey LogisticII model, due to having a high prediction accuracy and reliability, are far superior to the traditional GM(1,1) model. They play an important role in the restoration planning of coal mining.更多还原