鲸鱼优化算法在岩体结构面产状分组中的应用  

Application of Whale Optimization Algorithm on Orientation Grouping of Structural Planes in Rock masses

作　　者：王琦 王晓明 刘伟文 邵文娅 WANG Qi;WANG Xiaoming;LIU Weiwen;SHAO Wenya(Hebei GEO University,Shijiazhuang 050031,China;Hebei Technology Innovation Center for Intelligent Development and Control of Underground Built Environment,Hebei GEO University,Shijiazhuang 050031,China;Key Laboratory of Intelligent Detection and Equipment for Underground Space of Beijing-Tianjin-Hebei Urban Agglomeration,Ministry of Natural Resources,Shijiazhuang 050031,China)

机构地区：[1]河北地质大学城市地质与工程学院,河北石家庄050031 [2]河北省地下人工环境智慧开发与管控技术创新中心,河北石家庄050031 [3]京津冀城市群地下空间智能探测与装备重点实验室,河北石家庄050031

出　　处：《河北地质大学学报》2025年第2期13-20,共8页Journal of Hebei Geo University

基　　金：国家自然科学基金项目(41902298);河北省自然科学基金项目(D2019403151);河北地质大学国家预研项目(KY2024YB05)。

摘　　要：结构面分组是岩体工程勘查设计与稳定性分析的基础工作,分组结果的合理性和准确性直接关系到工程设计的科学性和安全性。传统的聚类算法如K-means聚类,虽然在一定程度上能够实现结构面的分组,但其聚类效果的精度和运算效率均存在不足。为此,提出了一种基于鲸鱼优化算法(WOA)的结构面产状分组方法。该方法将结构面分组问题视为一个最优化问题,通过构建合适的目标函数,利用WOA算法实现了结构面的自动分组。通过2个工程实例的对比分析,验证了WOA算法在收敛速度和达成率方面均优于粒子群优化算法(PSO)和花朵授粉算法(FPA)。本研究为结构面产状分组提供了一种新的方法,具有良好的工程应用前景。The grouping of structural planes is a fundamental task in the investigation,design,and stability analysis of rock mass engineering.The rationality and accuracy of the grouping results directly affect the scientific and safety aspects of engineering design.Traditional clustering algorithms,such as K-means clustering,can achieve the grouping of structural planes to some extent,but their clustering accuracy and computational efficiency are insufficient.To address this,this paper proposes a structural plane orientation grouping method based on the Whale Optimization Algorithm(WOA).This method treats the structural plane grouping problem as an optimization problem,constructing an appropriate objective function and utilizing the WOA algorithm to achieve automatic grouping of structural planes.Through comparative analysis of two engineering cases,it has been verified that the WOA algorithm outperforms the Particle Swarm Optimization(PSO)and Flower Pollination Algorithm(FPA)in terms of convergence speed and achievement rate.This study provides a new method for structural plane orientation grouping,demonstrating excellent prospects for engineering application.

关 键 词：鲸鱼优化算法 结构面产状 产状分组 轮廓系数 

分 类 号：TU45[建筑科学—岩土工程]