黄金科学技术 ›› 2019, Vol. 27 ›› Issue (6): 879-887.doi: 10.11872/j.issn.1005-2518.2019.06.879
Chaoqun HAN(),Jianhong CHEN(),Zhiyong ZHOU,Shan YANG
摘要:
矿岩可爆性等级的准确评判对爆破开挖设计以及岩土工程的安全稳定具有重要意义。通过综合考虑岩体固有属性与实际爆破效果对矿岩可爆性等级的影响,选取了岩体声波、波阻抗、爆破漏斗体积、大块率、小块率和平均合格率共6类指标,进行可爆性预测研究。为消除影响指标之间的信息重叠,针对55个矿岩样本数据集的大量信息,采用主成分分析法降维,提取得到包含98.38%原始信息的4类主成分,最后引入支持向量机模型对可爆性等级进行预测研究。研究结果表明:(1)与原始SVM模型相比,基于主成分分析法—支持向量机的预测模型不仅降低了数据的维度,同时使得矿岩可爆性等级预测准确率由78.5%提高至90.1%;(2)基于主成分分析法—支持向量机预测模型的评判结果与实际情况较为吻合,少量误判主要发生在部分特征差异性较小的矿岩样本之间。基于分层随机抽样技术的PCA-SVM预测模型,保证了训练集与测试集样本数据的随机性和差异性,对研究指标维数较多且部分指标间相关性较强的数据模型具有较强的适用性,对相似工程的研究具有一定的借鉴意义。
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