岩体结构面非典型数据集的优势组提取方法

doi:10.13722/j.cnki.jrme.2015.1177

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Abstract

The occurrence randomness of rock joints leads to generating large amounts of datum that do not belong to any dominant group in the practical datasets. This consequently causes the atypia of the data sets and the difficulty in determining dominant occurrences. In this study，A FCM-based dominant group determining method is developed，and a cut-back method is adopted to eliminate the influence of the data out of the dominant groups. Synthetic tests show that the suggested method is superior to the traditional FCM method for extracting dominant occurrences from atypical data sets. This method can not only eliminate unexpected data but also be able to obtain a high proportion of valid data and accurate dominant occurrences. Then optimal parameters for atypical data sets were obtained by comparing the performances of different distance functions with the cluster center expressions. A practical application of this method to a gold mine shows that the suggested method and the optimized parameters perform well in determining dominant rock joint groups from atypical data sets.

Key words： rock mechanics rock joints atypical data sets fuzzy C-mean clustering distance function clustering center algorithm cut-back method

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	Articles by authors
	LIU Kai
	LI Qiyue
	LI Xibing
	WANG Zewei

Cite this article:

LIU Kai,LI Qiyue,LI Xibing, et al. A dominant group determination method for atypical data sets of rock joint occurrences[J]. , 2017, 36(S2): 4018-4024.

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https://rockmech.whrsm.ac.cn/EN/10.13722/j.cnki.jrme.2015.1177 OR https://rockmech.whrsm.ac.cn/EN/Y2017/V36/IS2/4018

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