基于RBF神经网络的露天边坡优化设计方法

    A METHOD FOR DESIGNING AND OPTIMIZING THE OPEN-PIT SLOPE BASED ON RBF NEURAL NETWORKS

    • 摘要: 建立了岩质边坡稳定性定量评价的径向基函数(RBF)神经网络模型,避免了BP网络收敛速度慢的不足。提出了基于RBF神经网络的露天边坡优化设计方法,并将其应用于水厂铁矿边坡优化设计中,取得了良好的效果。

       

      Abstract: The RBF(Radial Basis Function)neural networks model for rock slope stability evaluation is built,which eliminates the slowly convergence speed of BP(Back Propagation)networks and gives an effective quantified method for evaluating the rock slope stability.A new method for designing and optimizing the open-pit slope based on RBF neural networks is proposed,which is applied to designing and optimizing ShuiChang Iron Mine open-pit slope angle.

       

    /

    返回文章
    返回