Estimation of radon as an earthquake precursor: A neural network approach |
| |
| Authors: | Dhawal Gupta and D T Shahani |
| |
| Institution: | (1) Department of Earth and Environmental Sciences, Institute of Land, Water and Environment , The Hashemite University, B. O. Box 150459, 13115 Zarqa, Jordan;(2) Department of Physics, Yarmouk University, Irbid, Jordan;(3) Department of Earth and Environmental Sciences, Yarmouk University, Irbid, Jordan |
| |
| Abstract: | An artificial neural networks (ANN) approach combined with Fourier Transform based selection of time period in the time series
Radon Emission Data has been presented and shown to improve event prediction rates and reduce false alarms in Earthquake Event
Identification over the traditional multiple linear regression techniques. The paper presents a neural networks system using
radial basis function (RBF) network as an alternative to traditional statistical regression technique in isolating Radon Emission
Anomaly caused by seismic activities. The RBF model has been developed to accept and predict earthquakes events based on a
known data set of Radon Emanation, Metrological parameters and actual earthquake events. Subsequently, the model was tested
and evaluated on a future data set and a prediction rate of 87.8%, if a reduced false alarm was achieved, the results obtained
are better than the traditional techniques. |
| |
| Keywords: | |
| 本文献已被 SpringerLink 等数据库收录！ |
|
