基于BP-遗传算法的排土场边坡几何参数优化

发布时间：2018-03-30 13:55

本文选题：排土场　切入点：边坡　出处：《矿冶工程》2017年02期

【摘要】：在保证矿山安全生产的前提下,为发挥排土场最大经济效益,提出了基于BP-遗传算法的排土场边坡几何参数优化方法。以弓长岭大阳沟排土场为例,借助极限平衡法获取研究所需数据,利用BP神经网络建立边坡坡角、单段台阶高度及相应的安全系数间的非线性关系,并以此关系式为边界约束条件,建立了优化边坡几何参数的数学模型,利用遗传算法和传统优化算法进行寻优。结果表明,与传统优化算法相比,BP-遗传算法的优化结果更加精确、可靠,有效避免了传统优化算法在寻优时易陷入局部最优解的问题。提供了一种简单、精确、可靠的排土场边坡几何参数优化方法,具有较好的应用前景。
[Abstract]:In order to give full play to the maximum economic benefit of the dump, a method of optimizing the geometric parameters of the dump slope based on BP- genetic algorithm is put forward under the premise of ensuring the safe production of the mine.Taking the Dayanggou dump in Gongchangling as an example, the data needed for the study are obtained by using the limit equilibrium method, and the nonlinear relationship between the slope angle, the height of the single step and the corresponding safety factor is established by using BP neural network.The mathematical model of optimizing the geometric parameters of slope is established by using this relation as the boundary constraint condition. The genetic algorithm and the traditional optimization algorithm are used to optimize the slope.The results show that the optimization results of BP- genetic algorithm are more accurate and reliable than those of the traditional optimization algorithm, and the problem that the traditional optimization algorithm is prone to fall into the local optimal solution is avoided effectively.A simple, accurate and reliable method for optimizing the geometric parameters of dump slope is provided, which has a good application prospect.
【作者单位】：辽宁科技大学矿业工程学院;辽宁科技大学土木工程学院;
【基金】：国家自然科学基金(51274053) 辽宁省教育厅科研基金(L2011040)
【分类号】：TD854.7

【相似文献】