基于DBSCAN选择性聚类集成的岩体结构面优势产状分组方法

Dominant partitioning method of rock mass discontinuity based on DBSCAN selective clustering ensemble

针对单个结构面聚类模型存在误判或漏选风险、难以有效识别噪点与孤值等问题,提出利用具有噪声的基于密度的聚类(DBSCAN)算法进行选择性聚类集成的岩体结构面优势产状分组方法。首先,将结构面产状进行空间坐标转换,以单位法向量的夹角正弦值作为相似性度量标准。进而,基于DBSCAN算法构建一定数量具有差异性的基聚类器,借助选择性聚类集成技术挑选出部分优异的基聚类器。最后采用一致性集成技术融合这些基聚类器,获得一个高可靠度的选择性聚类集成结果。将该方法应用于DIPS软件数据集与松塔水电站坝址区结构面勘察中,检验了该方法的可行性与有效性。研究结果表明:该方法聚类效果显著优于常见聚类算法,聚类结果客观合理,不仅能有效标识出噪点与孤值,还克服了单个模型易过分割或欠分割的不足。该研究成果对准确确定结构面优势组具有一定的工程价值。

For the problems existing in the traditional single discontinuity based clustering model,such as the risk of misclassification or omission and the inability to identify noise and isolated values,a dominant partitioning method of rock mass discontinuity based on selective clustering ensemble using density-based spatial clustering of applications with noise(DBSCAN)algorithm is proposed.Firstly,the spatial coordinate transformation is performed with the attitude of discontinuity,and the sine of the angle between the unit normal vectors is defined as similarity measurement.Then,a certain number of different base clusters are constructed based on the DBSCAN algorithm,with the selective clustering ensemble technology,some excellent base clusters are selected.Finally,the consistent ensemble technology is used to fuse these base clusters to generate a highly reliable selective clustering ensemble result.The DIPS software data set and the discontinuity survey result in the dam site area of Songta hydropower station are used to test the feasibility and effectiveness of the proposed method.The research results show that the clustering effect of the proposed method is significantly better than that of common clustering algorithms.The clustering results are objective and reasonable.It not only effectively identifies noise and isolated values,but also overcomes the shortcomings of over-segmentation or under-segmentation of the single discontinuity based clustering model.The research results are valuable in accurately determining the dominant group of discontinuity.