中南大学学报（自然科学版）2011，Vol.42Issue(10)：3189-3194,6.
粗糙集-BP神经网络组合方法及其应用
Method of rough sets-back propagation neural network and its application to identification of surrounding rock stability
摘要
Abstract
Combining neural network with data mining, the identifying method of surrounding rock stability was brought forward. Firstly, a knowledge expression system based on information database of Yanzhou Coal Minerial roadway was founded, and its data were discretized. Secondly, aiming at the defects of traditional BP neural network, namely slow convergence, poor fault tolerance and inconsistent result, decision table was obtained by rough sets data analysis program compiled by MATLAB software; afterwards, decision knowledge was used to conduct constitution of neural network and training samples selection. In the end, the stability of surrounding rock was studied. The results show that this method conquers many disadvantages of traditional BP neural network, and possesses many merits, such as well fault tolerance, fast education speed, high precision, good universal approximation, and so on. Therefore, it can be preferably used to identify the stability of surrounding rock.关键词
粗糙集/BP神经网络/数据挖掘/MATLAB软件/围岩稳定性判别Key words
rough sets/ BP neural network/ data mining/ MATLAB software/ identification of surrounding rock stability分类
矿业与冶金引用本文复制引用
姜安龙,戚玉亮..粗糙集-BP神经网络组合方法及其应用[J].中南大学学报（自然科学版）,2011,42(10):3189-3194,6.基金项目
江西省教育厅科研基金资助项目(GJJ09493) （GJJ09493）
南昌航空大学博士启动基金资助项目(EA200911023) （EA200911023）
南昌航空大学科技创新团队项目(EB200911299) （EB200911299）
