• DocumentCode
    2247200
  • Title

    Determining the angles of break of the mining subsidence basin by the neural network with genetic algorithm

  • Author

    Chai Hua-bin

  • Author_Institution
    State Bur. of Surveying & Mapping Key Lab. of Mine Spatial Inf. Technol., Henan Polytech. Univ., Jiaozuo, China
  • Volume
    3
  • fYear
    2010
  • fDate
    6-7 March 2010
  • Firstpage
    185
  • Lastpage
    187
  • Abstract
    The angle of break is a key factor that determines the mining damage extent of the surface in a mine, and it is also used to depict the characteristics of the mining subsidence basin. The geological and mining factors that influence the angle of break are fully analyzed. Based on the practical observational data from the ground movement monitoring stations of many mines in China, a neural network model with genetic algorithm is developed to determine the angle of break. The combination of genetic algorithm and neural network can overcome the disadvantages of the artificial neural works such as limitation of local optimization and slow convergence rate. The validity and reliability of neural network method combined with genetic algorithm to determinate the angle of break are verified by the existing engineering instances.
  • Keywords
    genetic algorithms; mining; neural nets; break angle determination; genetic algorithm; geological factors; mining factors; mining subsidence basin; neural network; Artificial neural networks; Data engineering; Genetic algorithms; Genetic engineering; Geology; Monitoring; Neural networks; Robotics and automation; Surface cracks; Tensile strain; angle of break; genetic algorithm; neural network; subsidence basin;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Informatics in Control, Automation and Robotics (CAR), 2010 2nd International Asia Conference on
  • Conference_Location
    Wuhan
  • ISSN
    1948-3414
  • Print_ISBN
    978-1-4244-5192-0
  • Electronic_ISBN
    1948-3414
  • Type

    conf

  • DOI
    10.1109/CAR.2010.5456660
  • Filename
    5456660