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
Link To Document