Earthquake Magnitude Prediction in Chile Using Neural Network
- Resource Type
- Conference
- Authors
- Bharadwaj, Rohit K; Pasari, Sumanta; Devi, Sonu
- Source
- 2022 IEEE 7th International Conference on Recent Advances and Innovations in Engineering (ICRAIE) Recent Advances and Innovations in Engineering (ICRAIE), 2022 IEEE 7th International Conference on. 7:294-297 Dec, 2022
- Subject
- Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Photonics and Electrooptics
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Performance evaluation
Technological innovation
Earthquakes
Neural networks
Predictive models
earthquake prediction
neural network
time series
- Language
In this study, we implement an earthquake magnitude prediction model using a neural network for a test region in Chile. For this, the epicenter of earthquake is located on a mesh with dimensions of 1°×1°. We adopt a zonation scheme originally proposed by Reyes and Cardenas [1]. The scheme uses increments in b−value and other input parameters to incorporate G-R linear relation and Bath’s law. The model enables the prediction of the maximum magnitude for a given cell within the next five days. Common seismological parameters are used for the performance evaluation of the model. Results show satisfactory performance of the proposed model in comparison to other existing models.