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A platform for research: civil engineering, architecture and urbanism
Fuzzy C-means clustering analysis based on quantum particle swarm optimization algorithm for the grouping of rock discontinuity sets
Abstract Rock discontinuities significantly influence the deformation as well as strength of rock masses. One of the basic analyses for rock engineering is categorizing discontinuities with similar orientations into groups. In this study, an improved FCM method is proposed to identify rock discontinuity sets automatically. The method is established on account of quantum particle swarm optimization, which could achieve the global optimization as well as becomes insensitive to the initial cluster centers. Benchmark case with artificial data and discontinuity data exposed from the Songta dam area are utilized to test the validity of the new algorithm. The test results demonstrate that the new algorithm could well divide discontinuity data. The grouping results acquired by the new algorithm are similar to those of several other methods, which are commonly used to divide discontinuity sets. The main advantage of this method is that achieves a global optimum without selecting proper initial cluster centers.
Fuzzy C-means clustering analysis based on quantum particle swarm optimization algorithm for the grouping of rock discontinuity sets
Abstract Rock discontinuities significantly influence the deformation as well as strength of rock masses. One of the basic analyses for rock engineering is categorizing discontinuities with similar orientations into groups. In this study, an improved FCM method is proposed to identify rock discontinuity sets automatically. The method is established on account of quantum particle swarm optimization, which could achieve the global optimization as well as becomes insensitive to the initial cluster centers. Benchmark case with artificial data and discontinuity data exposed from the Songta dam area are utilized to test the validity of the new algorithm. The test results demonstrate that the new algorithm could well divide discontinuity data. The grouping results acquired by the new algorithm are similar to those of several other methods, which are commonly used to divide discontinuity sets. The main advantage of this method is that achieves a global optimum without selecting proper initial cluster centers.
Fuzzy C-means clustering analysis based on quantum particle swarm optimization algorithm for the grouping of rock discontinuity sets
Song, Shengyuan (author) / Wang, Qing (author) / Chen, Jianping (author) / Li, Yanyan (author) / Zhang, Wen (author) / Ruan, Yunkai (author)
KSCE Journal of Civil Engineering ; 21 ; 1115-1122
2016-11-04
8 pages
Article (Journal)
Electronic Resource
English
| British Library Online Contents | 2015