| 神经网络和模糊综合评判在边坡稳定性分析中的应用比较 |
| |
| 引用本文： | 黄永刚,张学焱,李雪珍,饶运章. 神经网络和模糊综合评判在边坡稳定性分析中的应用比较[J]. 有色金属科学与工程, 2016, 7(3): 94-99. DOI: 10.13264/j.cnki.ysjskx.2016.03.017 |
| |
| 作者姓名： | 黄永刚 张学焱 李雪珍 饶运章 |
| |
| 作者单位： | 江西理工大学资源与环境工程学院，江西 赣州 341000 |
| |
| 基金项目： | 2011年度江西省安全生产重大课题(JXAJ2011002) |
| |
| 摘 要： | 采用BP神经网络和模糊综合评判两种方法应用预测边坡稳定性，选取摩擦角、内聚力、重度、边坡角、孔隙压力比、边坡高度6个指标作为评价因子，结合60个边坡实例，分别采用BP神经网络和模糊综合评判对样本边坡进行稳定性评价. 对两者预测结果的优劣性进行评判，结果表明BP神经网络评判结果精度更高，模糊综合评判则可以较好地实现评判等级划分.
|
| 关 键 词： | 神经网络 模糊综合评判 边坡稳定性 BP 稳定性等级 |
| 收稿时间： | 2015-07-27 |
Contrastive application of neural network and fuzzy comprehensive evaluation to slope stability analysis |
| |
| Affiliation: | School of Resources and Environmental Engineering, Jiangxi University of Science and Technology, Ganzhou 341000, China |
| |
| Abstract: | The BP neural network and fuzzy comprehensive evaluation were used to predict slope stability and the 6 indexes, such as friction angle, cohesive force, severe, slope angle, pore pressure ratio and slope height were used as the evaluation factors. The stability of the slope was respective evaluated by using BP neural network and fuzzy comprehensive evaluation combining with the examples of 60 slopes. The results show that the accuracy of BP neural network is more accurate, and the fuzzy comprehensive evaluation can be used to achieve the classification of evaluation. |
| |
| Keywords: | neural network fuzzy comprehensive evaluation slope stability BP stability grade |
| 本文献已被 万方数据 等数据库收录！ |
| 点击此处可从《有色金属科学与工程》浏览原始摘要信息 |
|
点击此处可从《有色金属科学与工程》下载全文 |
