Evaluation on stability of stope structure based on nonlinear dynamics of coupling artificial neural network

被引:0
|
作者
Cai, Meifeng [1 ]
Lai, Xingping [1 ]
机构
[1] Civil and Environ. Eng. Sch., Univ. of Sci. and Technol. Beijing, Beijing 100083, China
关键词
Dynamics - Evaluation - Neural networks - Stability - Stoping - Structures (built objects);
D O I
暂无
中图分类号
学科分类号
摘要
The nonlinear dynamical behaviors of artificial network (ANN) and their application to science and engineering were summarized. The mechanism of two kinds of dynamical processes, i.e. weight dynamics and activation dynamics in neural networks, and the stability of computing in structural analysis and design were stated briefly. It was successfully applied to nonlinear neural network to evaluate the stability of underground stope structure in a gold mine. With the application of BP network, it is proven that the neuro-computing is a practical and advanced tool for solving large-scale underground rock engineering problems.
引用
收藏
页码:1 / 4
相关论文
共 50 条
  • [1] Evaluation on stability of stope structure based on nonlinear dynamics of coupling artificial neural network
    Cai, MF
    Lai, XP
    JOURNAL OF UNIVERSITY OF SCIENCE AND TECHNOLOGY BEIJING, 2002, 9 (01): : 1 - 4
  • [2] Factors analysis of dynamic stability of stope roof with artificial neural network
    Ling, BC
    Cheng, GY
    PROGRESS IN SAFETY SCIENCE AND TECHNOLOGY, VOL 4, PTS A and B, 2004, 4 : 1805 - 1808
  • [3] Application of nonlinear neural network to analyze the stope structure parameters
    Lai, X.-P.
    Cai, M.-F.
    Zhang, B.-C.
    Meitan Xuebao/Journal of China Coal Society, 2001, 26 (03): : 245 - 248
  • [4] Artificial neural network based voltage stability evaluation
    Modi, PK
    Singh, SP
    Sharma, J
    Proceedings of the IASTED International Conference on Artificial Intelligence and Applications, Vols 1and 2, 2004, : 888 - 893
  • [5] Grid Search Optimised Artificial Neural Network for Open Stope Stability Prediction
    Erdogan Erten, Gamze
    Bozkurt Keser, Sinem
    Yavuz, Mahmut
    INTERNATIONAL JOURNAL OF MINING RECLAMATION AND ENVIRONMENT, 2021, 35 (08) : 600 - 617
  • [6] Quantitative evaluation of mining structure based on the artificial neural network
    Zhu, Bao-Long
    Xia, Yu-Cheng
    Meitiandizhi Yu Kantan/Coal Geology & Exploration, 2001, 29 (06):
  • [7] A nonlinear perturbation model based on artificial neural network
    Pang, Bo
    Guo, Shenglian
    Xiong, Lihua
    Li, Chaoqun
    JOURNAL OF HYDROLOGY, 2007, 333 (2-4) : 504 - 516
  • [8] ARTIFICIAL NEURAL NETWORK BASED ASSEMBLABILITY EVALUATION
    杨建国
    马瑞晓
    陈瑞琪
    Journal of China Textile University(English Edition), 1997, (04) : 54 - 59
  • [9] Dynamics of a hybrid system of a brain neural network and an artificial nonlinear oscillator
    Katayama, N
    Nakao, M
    Saitoh, H
    Yamamoto, M
    BIOSYSTEMS, 2000, 58 (1-3) : 249 - 257
  • [10] MODELING THE COUPLING OF REINFORCEMENT IN CONCRETE BASED ON AN ARTIFICIAL NEURAL NETWORK
    Nikolyukin, A. N.
    Yartsev, V. P.
    Bondarev, B. A.
    Korneev, A. O.
    RUSSIAN JOURNAL OF BUILDING CONSTRUCTION AND ARCHITECTURE, 2019, (03): : 6 - 16