2018
DOI: 10.14311/nnw.2018.28.009
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Large Earthquake Magnitude Prediction in Taiwan Based on Deep Learning Neural Network

Abstract: In this paper, a deep learning-based method for earthquake prediction is proposed. Large-magnitude earthquakes and tsunamis triggered by earthquakes can kill thousands of people and cause millions of dollars worth of economic losses. The accurate prediction of large-magnitude earthquakes is a worldwide problem. In recent years, deep learning technology that can automatically extract features from mass data has been applied in image recognition, natural language processing, object recognition, etc., with great … Show more

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Cited by 61 publications
(27 citation statements)
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“…The DL net gradually optimizes these parameters during the training process so as to establish an incomprehensible mapping from input to output [ 34 ]. Therefore, it has been widely used in earthquake monitoring with a great performance in recent years [ 35 , 36 ]. In fact, DL had been used to extract deep information, which may cause some information loss [ 19 ].…”
Section: Cnn Networkmentioning
confidence: 99%
“…The DL net gradually optimizes these parameters during the training process so as to establish an incomprehensible mapping from input to output [ 34 ]. Therefore, it has been widely used in earthquake monitoring with a great performance in recent years [ 35 , 36 ]. In fact, DL had been used to extract deep information, which may cause some information loss [ 19 ].…”
Section: Cnn Networkmentioning
confidence: 99%
“…The above-mentioned earthquake prediction using RNN was primarily based on the hierarchical model of vector point objects to organize the spatiotemporal data of earthquakes. Huang et al [22] organized the historical earthquake data of the entire Taiwan Province using the raster model. The study area was divided into 256 × 256 square sub-regions.…”
Section: Of 23mentioning
confidence: 99%
“…In 2015, for the expert system can provide the characteristics of flexible and effective solutions to different problems, the association rules were used for historical seismic data processing, and the expert systems based on association rules were applied to forecast the earthquake probability over the next 12 hours [5]. Huang et al [23] proposed a deep learning approach to predict continuous earthquake. For current neural networks are prone to local minimum problems during the training phase, some scholars use optimization algorithms such as genetic algorithms to optimize neural networks [6,21,22].…”
Section: Related Workmentioning
confidence: 99%