中国科技核心期刊
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正交试验-M-P法-多元线性回归高边坡稳定性预测模型
- 作者：
方健|方庆红|李 京
- 作者单位：
- （1. 广东宏通绿色矿业有限公司；2. 长沙矿山研究院有限责任公司； 3. 武汉科技大学资源与环境工程学院）
基金项目：
- 国家自然科学基金项目（42307252）
详细信息：
- 作者简介：
- 方健（1984—），男，工程师，从事矿山开采、矿业管理等工作；E-mail：179763871@qq. com
- 通讯作者：
- 方庆红（1995—），男，工程师，硕士，从事矿业工程开采咨询、设计及研究工作；E-mail：884582880@qq. com
- PDF下载
Prediction model for high slope stability based on orthogonal test, M-P method, and multiple regression
- English Author：
Fang Jian¹, Fang Qinghong², Li Jing³
- Unit：
- （1. Guangdong Hongtong Green Mining Co., Ltd.; 2. Changsha Institute of Mining Research Co., Ltd.; 3. School of Resources and Environmental Engineering, Wuhan University of Science and Technology）
- 摘要
- 在线预览
- 参考文献
摘要:
为快速准确计算露天矿山边坡稳定性系数及预测边玻安全，利用M-P法计算正交试验设计方案的稳定性系数，采用多元线性回归，开展高边坡稳定性预测模型研究，提出高边坡稳定性简化预测模型，并验证模型预测效果；揭示边坡稳定性简化计算方法原理，探讨边坡稳定性影响因素与稳定性系数之间的定量关系；揭露因素指标对边玻稳定性影响程度，修正预测模型，并采用强度折减法对修正后的预测模型进行应用验证。研究结果表明：修正后预测模型预测结果相对误差平均值为2.48%，预测精度和拟合度均较高；7种因素指标对边坡稳定性影响程度为p>C>a>p>H> E>u，其中，弹性模量和泊松比几乎无影响；应用强度折减法验证，得出修正后的预测模型科学合理。该模型可为高边坡安全预警和防控提供一定的参考。
关键词:
高边坡稳定性；正交试验；M-P法；多元线性回归；强度折减法；预测模型
Abstract:
To quickly and accurately calculate slope stability factors in open-pit mines and predict slope safety, the M-P method was utilized to calculate the stability factors of orthogonal test design. A multiple linear regression approach was employed to develop a predictive model for high slope stability, proposing a simplified prediction model and validating its accuracy. The study revealed the principle behind simplified stability calculations, explored the quan-titative relationships between influencing factors and stability factors, and assessed the influence of specific factors on slope stability. The prediction model was further refined and validated using the strength reduction method. Results showed that the average relative error of the refined prediction model was 2.48 %, indicating high prediction accuracy and model fit. Among 7 influencing factors, the impact degree on slope stability was o > C > a > p > H >E > u, where elas-tic modulus and Poisson's ratio had negligible effects. The validation using the strength reduction method confirmed the scientific robustness of the refined prediction model. This model provides reference for slope safety early warning and control measures.
Keywords:
high slope stability; orthogonal test; M-P method; multiple linear regression; strength reduction method; prediction model
