Version 1
: Received: 21 August 2017 / Approved: 21 August 2017 / Online: 21 August 2017 (09:55:55 CEST)
How to cite:
Ghorbani, S.; Barari, M.; Hosseini, M. Provision of a New Method to Improve the Detection of Micro Seismic Events. Preprints2017, 2017080071. https://doi.org/10.20944/preprints201708.0071.v1
Ghorbani, S.; Barari, M.; Hosseini, M. Provision of a New Method to Improve the Detection of Micro Seismic Events. Preprints 2017, 2017080071. https://doi.org/10.20944/preprints201708.0071.v1
Ghorbani, S.; Barari, M.; Hosseini, M. Provision of a New Method to Improve the Detection of Micro Seismic Events. Preprints2017, 2017080071. https://doi.org/10.20944/preprints201708.0071.v1
APA Style
Ghorbani, S., Barari, M., & Hosseini, M. (2017). Provision of a New Method to Improve the Detection of Micro Seismic Events. Preprints. https://doi.org/10.20944/preprints201708.0071.v1
Chicago/Turabian Style
Ghorbani, S., Morteza Barari and Mojtaba Hosseini. 2017 "Provision of a New Method to Improve the Detection of Micro Seismic Events" Preprints. https://doi.org/10.20944/preprints201708.0071.v1
Abstract
Natural events such as floods, fires, tsunamis, earthquakes and others have nowadays caused serious damage to human beings and nature. The precise detection of these natural events and especially the earthquake has nowadays become the focus of many computer and geoscientific researchers. Computer science and machine learning algorithms have revolutionized early detection and prediction of these events. Hence, a fuzzy method has been initially used in this article to enhance the authenticity of data based on application of effective variables and then combination of neural network algorithms of the MLP perceptron and radial network of RBF in form of a collective learning system in order to more accurately identify seismic events on a small scale. It was observed after simulating the proposed method that the proposed method has significantly improved based on actual error and root-mean-square error (RMSE) criteria compared to basic methods.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
