Traditional coal mine safety prediction methods are off-line and do not have dynamic prediction functions.The Support Vector Machine(SVM) is a new machine learning algorithm that has excellent properties.The least squ...Traditional coal mine safety prediction methods are off-line and do not have dynamic prediction functions.The Support Vector Machine(SVM) is a new machine learning algorithm that has excellent properties.The least squares support vector machine(LS-SVM) algorithm is an improved algorithm of SVM.But the common LS-SVM algorithm,used directly in safety predictions,has some problems.We have first studied gas prediction problems and the basic theory of LS-SVM.Given these problems,we have investigated the affect of the time factor about safety prediction and present an on-line prediction algorithm,based on LS-SVM.Finally,given our observed data,we used the on-line algorithm to predict gas emissions and used other related algorithm to compare its performance.The simulation results have verified the validity of the new algorithm.展开更多
Prediction of methane emissions at the stage of longwall planning constitutes the basis for the determination of the appropriate method and parameters of ventilation and selection of prevention means including the met...Prediction of methane emissions at the stage of longwall planning constitutes the basis for the determination of the appropriate method and parameters of ventilation and selection of prevention means including the methane drainage technol- ogy. The growth of methane saturation of coal seams with the extraction depth, with simultaneously increasing output concen- tration, contributes to the increase of the quantity of methane emitted into longwall areas. The subject matter of the article has been directed at the predicted quantity of methane emissions into planned longwalls with roof caving in the layer of seams adjacent to the roof of large thickness. The performed prognostic calculations of methane emissions into the longwall working were referred to two sources, i.e. methane liberated during coal mining by means of a cutter-loader and methane originating from the degasification of the floor layer destressed by the longwall conducted in the close-to-roof layer. The calculations of predictions allow to refer to the planned longwall, on account of the emitting methane, with possible and safe output quantity. Planning of extraction in the close-to-roof layer of a seam of large thickness with roof caving is especially important in con- ditions of increasing methane saturation with the depth of deposition and should be preceded by a prognostic analysis for de- termining the extraction possibilities of the planned longwall.展开更多
文摘Traditional coal mine safety prediction methods are off-line and do not have dynamic prediction functions.The Support Vector Machine(SVM) is a new machine learning algorithm that has excellent properties.The least squares support vector machine(LS-SVM) algorithm is an improved algorithm of SVM.But the common LS-SVM algorithm,used directly in safety predictions,has some problems.We have first studied gas prediction problems and the basic theory of LS-SVM.Given these problems,we have investigated the affect of the time factor about safety prediction and present an on-line prediction algorithm,based on LS-SVM.Finally,given our observed data,we used the on-line algorithm to predict gas emissions and used other related algorithm to compare its performance.The simulation results have verified the validity of the new algorithm.
文摘Prediction of methane emissions at the stage of longwall planning constitutes the basis for the determination of the appropriate method and parameters of ventilation and selection of prevention means including the methane drainage technol- ogy. The growth of methane saturation of coal seams with the extraction depth, with simultaneously increasing output concen- tration, contributes to the increase of the quantity of methane emitted into longwall areas. The subject matter of the article has been directed at the predicted quantity of methane emissions into planned longwalls with roof caving in the layer of seams adjacent to the roof of large thickness. The performed prognostic calculations of methane emissions into the longwall working were referred to two sources, i.e. methane liberated during coal mining by means of a cutter-loader and methane originating from the degasification of the floor layer destressed by the longwall conducted in the close-to-roof layer. The calculations of predictions allow to refer to the planned longwall, on account of the emitting methane, with possible and safe output quantity. Planning of extraction in the close-to-roof layer of a seam of large thickness with roof caving is especially important in con- ditions of increasing methane saturation with the depth of deposition and should be preceded by a prognostic analysis for de- termining the extraction possibilities of the planned longwall.
