Bioinspired Early Prediction of Earthquakes Inferred by an Evolving Fuzzy Neural Network Paradigm.

Communications in Computer and Information Science(2019)

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Abstract
Earthquakes could be early predicted as demonstrated by animal's behavior that are able to detect the leading wave part of the seismic wave (the P-wave). P-waves travel faster than S-wave wave (the shaking wave), so they reach the seismic sensors early (tens of seconds to minutes in advance) compared to the P-wave. A bioinspired framework could be implemented mimicking the animal's behaviour related to the event of an incoming earthquake. Training a Fuzzy Neural Network to recognize the P-waves, early prediction of earthquakes is feasible and an adequate recovery strategy could be implemented. A technological motivation is the availability of OTS (off-the-shelf) vibration sensors and the fast development of IoT (Internet of Things) toward the new paradigm IoE (Internet of Everything).
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Key words
Earthquake,Seimic waves,EFuNN,Biomimetic,Early prediction,Vibration sensor,Internet of Everything
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