摘要
由于露天矿边坡具有地形复杂、高低起伏等特点,针对传统边坡可视化的研究方法存在一定的局限性问题,在此提出基于BP神经网络的露天矿边坡三维可视化研究算法。将露天矿边坡进行三维可视化,剥离等高线并进行赋值。利用BP神经网络,建立等高线预测模型,生成栅格DEM矩阵,实现可视化建模。实验结果表明,该算法模型解决了边坡复杂性问题,克服了传统可视化方法局限性,真实准确地模拟了现实中边坡的多样性,验证了该方法的有效性。
A method of researching strip-mine slope′s 3D visualization based on BP is proposed according to the problem that traditional visual research methods have limitation caused by strip-mine slope＆#39;s characteristic of complex terrain. The 3D vi-sualization of strip-mine slope is performed,its contour is assigned,and then the visual contour prediction model is built with BP neural network to generate a grid DEM matrix. The experiment results show that the problem of strip-mine slope＆#39;s com-plexion can be solved by this model,the limitation of traditional methods can be overcome,and the strip-mine slope’s diversity can be simulated truly. The validity of the method was verified by the experiment.
出处
《现代电子技术》
2014年第10期53-55,共3页
Modern Electronics Technique
基金
国家自然科学基金资助项目(60443004)
