使用元启发式算法评估RMR与岩石质波速的相关性
Pouya Koureh Davoodi1, Farnusch Hajizadeh1, Mohammad Rezaei2
1Department of Mining Engineering, Faculty of Engineering, Urmia University, Urmia, Iran.
Scientific reports
|May 21, 2025
概括
本研究介绍了使用地震波速度 (Vp和Vs) 确定岩石质量评级 (RMR) 的非破坏性方法. 一个混合TRR-GA模型被证明是最有效的准确的RMR预测.
科学领域:
- 地质技术工程 地质技术工程
- 岩石机械学 岩石机械学
- 应用地质物理学应用地质物理学
背景情况:
- 岩石质量评分 (RMR) 对于岩石工程设计至关重要.
- 传统的RMR确定是破坏性的,昂贵的,耗时的.
- 使用易于测量的参数的非破坏性方法提供了一个经济的替代方案.
研究的目的:
- 评估RMR和地震波速度 (Vp和Vs) 之间的关系.
- 开发和比较用于RMR预测的非破坏性模型.
- 用Vp和Vs来确定RMR最准确的预测模型.
主要方法:
- 分析了150个不同类型岩石的现场数据集.
- 基因算法 (GA),信任区域反射 (TRR) 和混合TRR-GA模型的应用.
- 使用随机森林 (RF) 分析和各种性能指标 (散射图,错误组图,泰勒图,RER曲线) 的验证.
主要成果:
- 同时使用Vp和Vs对于RMR的确定比单个参数更可靠.
- 所有提出的模型 (GA,TRR,TRR-GA) 在预测RMR方面都表现出高准确度.
- 混合型TRR-GA模型在基于Vp和Vs的RMR预测方面表现出卓越的性能.
结论:
- 混合TRR-GA模型提供了一个强大的,非破坏性的,准确的方法来确定RMR.
- 使用具有成本效益的地震速度 (Vp,Vs) 和元启发式算法可以提高RMR评估.
- 为了实际应用,建议使用更大的数据集和各种岩石类型进行进一步的验证.
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