基于模糊聚类及BP神经网络的采矿方法选择研究

Mining method optimization based on the fuzzy clustering and the BP neural network

以某铁矿为工程背景,采用模糊聚类分析的方法对采矿方法进行初选,建立了模糊聚类初选采矿方法可行方案集,通过模糊动态聚类分析,得到了初选方案。基于BP神经网络的方法预测了初选方案的技术经济指标,运用层次分析法,综合考虑经济因素、资源利用率、劳动生产率、安全因素、合理程度五大类因素,构建了采矿方法优选的评价指标体系,最终通过模糊数学综合评判,选取了最优采矿方法。

Adopt the method of fuzzy cluster analysis for primary mining method with one Iron Mine as the engineering background,established mining programs for primary election,and obtained the primary solution by fuzzy dynamic cluster analysis.Based on BP neural network method,the primary scheme of technical and economic indicators was forecast.Using the analytic hierarchy process considering the economic factors,resource utilization,labor productivity,safety,the reasonable degree of five factors mining method selection of evaluation index system is were constructed.Finally,the optimal mining method was selected by fuzzy mathematical comprehensive evaluation.