BP神经网络在露天矿边坡位移预测中的应用

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英文篇名：Application of BP neural network in displacement prediction of mine slope 中文刊名：露天采矿技术 英文刊名：Opencast Coal Mining Technology 作者：王俊峰 ; 张丽英 英文作者：WANG Jun-feng ; ZHANG li-ying(Civil and Environmental Engineering School ; USTB ; Beijing 100083 ; China) 中文关键词：人工神经网络 ; 边坡 ; 预测 英文关键词：artificial neural networks(ANN) ; slope ; prediction 出版日期：2005-08-15 机构：北京科技大学土木与环境工程学院,北京科技大学土木与环境工程学院 北京100083 ,北京100083 年：2005 期：04 出版单位：露天采矿技术

摘要

随着露天矿开采深度的不断增加,矿山边坡高度也不断增加,随之而来的是对边坡稳定的维护与控制的难度大大增加。在全球卫星定位系统(GPS)所获得的露天矿边坡位移监测资料的基础上,应用BP神经网络模型对实测数据进行模拟计算和预测。分析结果表明,模型合理、可靠,精度较高。
With the mining depth of the strip mine and the height of the slopes increasing, difficulty of maintaining the stability and control of the slopes becomes bigger. This article based on lots of displacement date monitored by the Global Satellite Position System (GPS).On the basis of the neural network study, the BP neural network model is applied to slope displacement prediction of the mine. The analysis indicates that this model is rational and reliable ,the precision is high.

引文

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