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基于神经网络优化遗传算法的爆破参数优化

DOI: 10.13197/j.eeev.2014.01.257.cuitj.035, PP. 257-262

Keywords: 神经网络,遗传算法,采矿爆破,参数优化

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Abstract:

对于露天铁矿开采而言,爆破是一项重要且危险的开采活动。从安全的角度看,爆破的两种主要危害形式为超爆和飞石。影响爆破方案的因素有很多,包括矿石的自然属性和爆破方案等。对于同一矿场主要考虑的爆破方案参数包括炮眼深(HL)、间距(S)、装药深度(B)、阻塞深度(ST)、单位炸药消耗量(PF)和钻孔率(SD)。它们对超爆深度(BB)和飞石距离(FR)的影响是复杂的,非线性的。为了防止超爆和飞石造成事故,爆炸的参数必须在安全、经济的范围内。本文使用爆破影响因素和BB及FR分别作为神经网络(神经网络)的输入值和输出值加以训练,训练后的神经网络作为遗传算法(GA)的适应度函数。在使用GA寻找到最优的BB和FR,从而对爆破方案参数进行优化。结果表明该方法有效可行。

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