基于变权模型的煤层注水参数优化
首发时间:2022-06-14
摘要:粉尘灾害是煤矿主要灾害之一,煤层注水是减少粉尘悬浮的有效途径。为优化煤层注水参数,提高煤层注水防尘效果,建立了基于PSO-SVM与多准则决策的煤层注水评价模型。通过收集某矿的203组数据,分别作为训练集和测试集,利用粒子群算法优化SVM的初始参数,构建了基于PSO-SVM的湿润半径预测模型。将预测结果、煤层含水率增值、注水时间和注水压力作为多准则决策模型的评价指标,通过AHP与熵权法结合,对主客观权重进行分析,构建了基于非线性规划的组合赋权模型。最后,计算出在注水效果和经济效益两方面综合评分最高的参数。为研究矿井粉尘防治煤层注水参数的选取提供了参考。
关键词: 粉尘防治 粒子群算法 支持向量机 煤层注水 变权模型
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Parameter Optimization of coal seam water injection based on variable weight model
Abstract:The main disaster which makes an impact on safety production in the area of mine is dust disaster, pouring water into coal seam is an effective way that reduce the suspension of dust. We set up a model used as analysis and assessment that bases on PSO-SVM and multi criteria decision-making to explore the the details of pouring water into coal seam. By collecting 203 sets of data from a mine as training set and test set respectively, and using particle swarm optimization algorithm to optimize the initial parameters of SVM, a simulation and prediction model of wetting radius based on PSO-SVM is constructed. Finally, the parameters with the highest comprehensive score in water injection effect and economic benefit are calculated. Its provides a reference resource to the research that select parameters of coal seam water injection in mine dust\'s prevention and cure.
Keywords: dust prevention and control particle swarm optimization support vector machine coal seam water injection variable weight model
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