Estimation of Mining Tremor Occurrence by Using Neural Networks |
| |
| Authors: | V Rudajev R ?í? |
| |
| Institution: | (1) Center for Automation Research, University of Maryland, 20742 College Park, MD, USA;(2) NASA Goddard Space Flight Center, Computer Systems Research Facility, Code 635, 20771 Greenbelt, MD, USA;(3) Science Applications Research, 4400 Forbes Boulevard, 20706 Lanham, MD, USA;(4) Centre for Applied Research in Artificial Intelligence, Naval Research Laboratory, 20375 Washington, DC, USA;(5) Present address: Center for Computing and Applied Mathematics, National Institute of Standards and Technology, 20899 Gaithersburg, MD, USA;(6) Present address: Acoustics Division, Naval Research Laboratory, 20375 Washington, DC, USA; |
| |
| Abstract: | ?Changes of the primary strain-stress state (caused by interaction between natural conditions and mining activity) can result, under special circumstances, to the origin of seismic induced events. The question of induced seismic activity prediction was treated as a problem of time series extrapolation of maximum cumulative amplitudes and numbers of seismic events recorded per day. The treatment was carried out by means of Multilayered Perceptron Neural Networks (MLP NN). The application to mining tremor prediction has been tested and methodological conditions have been obtained. It was proved that the prediction of the number of mining tremors per day is more precise than the prediction of future energy (maximum amplitudes). Further advance, based on the processing of seismo-acoustic activity series, is introduced. |
| |
| Keywords: | |
| 本文献已被 SpringerLink 等数据库收录！ |
|
