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机构地区:[1]西南交通大学,成都610031 [2]中兴通讯股份有限公司,广东深圳518055
出 处:《路基工程》2018年第1期47-51,共5页Subgrade Engineering
摘 要:通过室内模型试验,研究了不同落石形状、质量、边坡覆盖层厚度对落石水平距离的影响程度。结果表明:形状对落石距离影响最大,质量无明显影响,边坡覆盖层在减少落石距离的同时也增加了变动区间。用偏移比公式对落石距离进行处理得到建议偏移比取值为0.3。将边坡平均坡度、边坡高度、坡面条件、落石质量、落石形状作为输入因子,运用BP神经网络模型进行预测,预测结果表明,该模型能很好地预测落石距离。With indoor model test, how rock shape, rock quality and slope cover thickness affect horizontal rockfall distance was studied herein. The result shows that, the rock shape has major effect on the rockfall distance, while the rock quality has minor effect; the slope cover decreases the rockfall distance and increases the variation zone at the same time. The recommended value of deviation ratio is 0. 3 when the rockfall distance is manipulated by deviation formula. Then the predication may be carried out by BP neutral network with average gradient of slope, height of slope, condition of slope surface, rock quality and rock shape taken as the input factors. The prediction results show that the model does well in prediction of rockfall distance.
关 键 词:模型试验 落石距离 影响因素 偏移比 BP神经网络
分 类 号:U411.93[交通运输工程—道路与铁道工程]
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