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在某露天矿由于爆破参数与岩石特性不相符合,导致爆破效果不是太好,大块率高,留有根底,炸药单耗偏高,大块率高势必会导致二次破碎的费用偏高,还会对铲装运输等后续程序产生影响,这都直接影响着矿山的经济效益。通过BP神经网络对矿山爆破参数进行优化,改善爆破效果,提高矿山的经济效益。
In an open-pit mine, the blasting effect is not very good due to the inconsistency between blasting parameters and rock characteristics, and the blasting effect is not very good. The boulder rate is high, leaving the bottom, the explosive unit consumption is high, the boulder rate is bound to lead to the high cost of secondary crushing , But also on the shovel transport and other follow-up procedures have an impact, which have a direct impact on the economic benefits of mines. BP neural network optimization of mine blasting parameters to improve the blasting effect and improve the economic benefits of the mine.