基于改进BP神经网络的围岩自稳能力评估模型  

Self-stability evaluation model of surrounding rock based on improved BP neural network

作　　者：王多点[1,2] 邱国庆[1] 戴婷婷[3] 王月[1] 

机构地区：[1]解放军理工大学工程兵工程学院 [2]66081部队 [3]中国卫星海上测控部

出　　处：《计算机应用》2012年第4期1056-1059,1063,共5页journal of Computer Applications

摘　　要：指挥防护工程是国家防护工程体系的重要组成部分。为提高其建设水平,采用改进的前馈(BP)神经网络,对指挥防护工程围岩自稳能力进行评估。结合指挥防护工程围岩的特点,设计评估网络拓扑结构。针对BP网络原始模型的缺陷改进,引入动量项、自适应调节学习率、陡度因子、可变隐层节点等,并采用遗传算法(GA)寻找最优的初始权值和阈值。最后结合实例对算法进行验证。结果表明,该模型科学可靠,具有较好的工程应用价值。Command protection engineering is the important component of national protection engineering system.To raise the level of construction of command protection engineering,the Back Propagation（BP） neural network was improved to give research on self-stability evaluation of its surrounding rock.Firstly,the network topology was devised,based on the characteristics of surrounding rock.Secondly,the model was improved according to its disadvantages,by introducing the momentum,self-adaptive adjusting learn rate,variable hidden nodes and steep factor;furthermore,Genetic Algorithm（GA） was imported to seek its best initial weight and threshold value.Finally,an instance was given to validate the algorithm.The results show that the model is scientifically reliable and of better value in engineering.

关 键 词：前馈神经网络 遗传算法 评估 围岩 自稳能力 指挥防护工程 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程] TP391.99[自动化与计算机技术—控制科学与工程]