In order to make better use of metal mineral resources,the overall dynamic optimization study of mine technology indexes was carried out.Firstly,the kernel density estimation method,BP neural network and exponential regression method were used to fit the relationship model of technical indicators respectively.Then,based on this,the overall dynamic optimization model was constructed,and the corresponding improved differential evolution algorithm was proposed.Finally,the established relationship model,optimization model and optimization algorithm were applied to Yinshan Copper Mine.The results show that the established relationship model has good fitting effect and high application value.The optimization results are in line with the actual situation of the mine,which verifies the effectiveness of the model and algorithm,and has a guiding role in mine production and planning.
关键词
金属矿山/技术指标/整体动态优化/IDE算法/核密度估计方法/BP神经网络
Key words
Metal mines/Technical indicators/Overall dynamic optimization/IDE algorithm/Kernel density estimation method/BP neural network
维普
万方数据