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- W2747698913 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." @default.
- W2747698913 created "2017-08-31" @default.
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- W2747698913 date "2017-08-21" @default.
- W2747698913 modified "2023-09-26" @default.
- W2747698913 title "Provision of a New Method to Improve the Detection of Micro Seismic Events" @default.
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- W2747698913 doi "https://doi.org/10.20944/preprints201708.0071.v1" @default.
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