Sparrow search algorithm-driven clustering analysis of rock mass discontinuity sets

作     者：Wu, Wenxuan Feng, Wenkai Yi, Xiaoyu Zhao, Jiachen Zhou, Yongjian 

作者机构：Chengdu Univ Technol State Key Lab Geohazard Prevent & Geoenvironm Prot Chengdu 610059 Peoples R China Chengdu Univ Technol Coll Environm & Civil Engn Chengdu 610059 Peoples R China 

出 版 物：《COMPUTATIONAL GEOSCIENCES》 (计算地球科学)

年 卷 期：2024年第28卷第4期

页      面：615-627页

核心收录：

学科分类：07[理学] 0708[理学-地球物理学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：National Natural Science Foundation of China National Natural Science Foundation of China [24NSFSC4865] Natural Science Foundation of Sichuan, China 

主　　题：Rock discontinuity Clustering analysis Sparrow search algorithm Silhouette coefficient 

摘      要：Rock discontinuity has a crucial impact on the deformation and strength of rock masses, and thus, the clustering of discontinuities is a critical aspect of rock mechanics. Traditional clustering methods require initial cluster centers to be specified and involve a multitude of parameter calculations, leading to a complex and cumbersome process. In this paper, a novel clustering approach based on the sparrow search algorithm (SSA) is introduced to overcome these limitations. This method utilizes a sparrow population coding technique and fitness function tailored to the unique characteristics of rock discontinuity orientation data. The SSA is adeptly applied to the clustering of rock joints, and the optimal number of clusters are automatically determined via the silhouette coefficient method. This methodology was tested on artificial datasets and actual discontinuity survey results from the underground powerhouse of the Henan Wuyue Hydropower Station to evaluate its feasibility and efficacy in analyzing rock discontinuities. Comparative data analysis reveals that the proposed method outperforms classic algorithms such as FCM and KPSO in terms of clustering accuracy and stability. The proposed method stands out among various clustering methods of discontinuity orientation for its ability to achieve convergent results without user intervention, demonstrating significant practical utility.