| BP网络在露天矿边坡角优化中的应用 |
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| 引用本文： | 何方维,朱明,刘文生,刘铁亮,王连海.BP网络在露天矿边坡角优化中的应用[J].金属矿山,2011,40(1):35-37. |
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| 作者姓名： | 何方维 朱明 刘文生 刘铁亮 王连海 |
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| 作者单位： | 1.河北联合大学；2.河北省矿业开发与安全技术重点实验室；3.唐山三友矿山有限公司 |
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| 摘 要： | 基于影响边坡稳定性的主要自然和工程因素，运用BP神经网络预测岩质边坡的稳定性，经大量样本进行网络训练，得出可靠的BP网络模型，预测露天矿最终边坡的最优化角度，并将结果与多元线性回归的预测角度比较。研究表明神经网络法具有精度高、收敛速度快、容错能力高等特点,能够满足实际工程的需要,是有一定实用价值和参考价值的边坡稳定性预测方法。
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| 关 键 词： | BP神经网络 多元回归 边坡稳定 预测 |
Application of BP Artifical Neural Network in Optimization of Open-pit Slope Angle |
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| He Fangwei,Zhu Ming,Liu Wensheng,Liu Tieliang,Wang Lianhai.Application of BP Artifical Neural Network in Optimization of Open-pit Slope Angle[J].Metal Mine,2011,40(1):35-37. |
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| Authors: | He Fangwei Zhu Ming Liu Wensheng Liu Tieliang Wang Lianhai |
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| Affiliation: | 1.Hebei Union University；2.Mining & Safety Technology Key Lab of Hebei Province；3. Tangshan Sanyou Mine Corporation; |
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| Abstract: | Based on the main natural and engineering factors affecting on slope stability, BP artificial neural network was applied to predict the stability of rock slope. After network training by a great deal of swatches, the reliable BP network model was elicited to forecast the optimum angle of final slope of mine, and the results were compared with the ones draw from multiple regression analysis. The study showed that the method of artificial neural network has characteristics of high precision, convergence rapidity and high fault tolerance capability, which can meet the need of slope stability prediction in engineering practice. |
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| Keywords: | BP artificial neural network Multiple Regression Slope stability Forecasting |
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