计算机应用 ›› 2012, Vol. 32 ›› Issue (04): 1056-1059.DOI: 10.3724/SP.J.1087.2012.01056

• 人工智能 • 上一篇    下一篇

基于改进BP神经网络的围岩自稳能力评估模型

王多点1,2,邱国庆2,戴婷婷3,王月2   

  1. 1. 66081部队,河北 怀来 050083
    2. 解放军理工大学 工程兵工程学院,南京 210007
    3. 中国卫星海上测控部,江苏 江阴 214431
  • 收稿日期:2011-09-26 修回日期:2011-11-21 发布日期:2012-04-20 出版日期:2012-04-01
  • 通讯作者: 王多点
  • 作者简介:王多点(1982-),男,山东苍山人,博士研究生,主要研究方向:军事运筹建模;
    邱国庆(1971-),男,湖南长沙人,讲师,硕士,主要研究方向:军事测绘、三维仿真;
    戴婷婷(1984-),女,安徽六安人,工程师,硕士,主要研究方向:军事建模与仿真;
    王月(1983-),女,辽宁铁岭人,硕士研究生,主要研究方向:作战模拟。

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

WANG Duo-dian1,2,QIU Guo-qing1,DAI Ting-ting3,WANG Yue1   

  1. 1. Engineering Institute of Corps of Engineers,PLA University of Science and Technology,Nanjing Jiangsu 210007,China
    2. Unit 66081 of PLA, Huailai Hebei 050083, China
    3. China Satellite Maritime Tracking and Controlling Department, Jiangyin Jiangsu 214431, China
  • Received:2011-09-26 Revised:2011-11-21 Online:2012-04-20 Published:2012-04-01
  • Contact: WANG Duo-dian

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。

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

Abstract: 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.

Key words: Back Propagation (BP) neural network, Genetic Algorithm (GA), evaluation, surrounding rock, self-stability, command protection engineering