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同一期地质运动中岩体所产生的结构面间距一般认为服从负指数分布。目前方法多根据产状单一因素进行分组,分组完成后同一组结构面的间距分布可能非常不规则,针对该问题,结合目前结构面采集到的数据质量高且具有空间位置等特点,提出一种新的双因素分组方法 (a new double-factor clustering method,NDCM)。分组时可综合考虑结构面产状与间距信息,该方法分组初值由模糊K均值法(fuzzy K-means)获取,通过调整隶属度较低的结构面分组编码达到修正结构面间距,使其满足负指数分布的目的。为获得NDCM的分组精度,进行了数值模型计算,该模型中结构面分组情况已知,利用模糊K均值法和NDCM法分别对此模型进行结构面分组。对比结果表明,NDCM法分组精度明显优于模糊K均值分组方法;重叠率越高组数越多这种优势越明显;相比于模糊K均值法,NDCM分组精度平均可以提升0.06左右。
In the same period of geologic movement, the spacing of structural planes produced by rock mass is generally considered as obeying negative exponential distribution. At present, the methods are mostly grouped according to the single factor of the producing condition. After the grouping is completed, the spacing distribution of the same set of structural planes may be very irregular. According to the characteristics of the data collected in the structural plane with high spatial quality and spatial structure, A new double-factor clustering method (NDCM). The grouping can take into account the information about the shape and spacing of structural plane. The initial value of the grouping is obtained by fuzzy K-means. By adjusting the encoding of the structural facets with lower membership degree to the corrected structural plane spacing, To meet the purpose of negative index distribution. In order to obtain the grouping precision of NDCM, the numerical model calculation is carried out. In this model, the structural surface grouping is known, and the structural surface grouping is carried out by using fuzzy K-means and NDCM respectively. The comparison results show that the accuracy of NDCM grouping is better than that of fuzzy K-means grouping. The higher the overlapping rate is, the more the group number is. The more the NDCM grouping accuracy can be improved about 0.06 compared with the fuzzy K-means method.