Detecting seismic frequency occur based on motif discovery approach
Detection and prediction of seismic are important problems have extensive application in many areas such as predict earthquakes, tsunamis in geography, architecture..., especially in the traffic construction domain. Researching to find out the effective seismic prediction and detection method with high accuracy is a hot trend both in Vietnam and the world. The survey phased of seismic characteristics before starting a project on traffic construction is vital. The next tasks include time series classification, frequent sequence pattern recognition, abnormal detection, and time series prediction. Motif detection in time series data has received significant recognition in the data mining community since its genesis, mainly because, motif discovery is both meaningful and more probable to succeed on big data. In this paper, the motif detection problem will be used to predict the most frequent seismic frequency. This method is being applied in many fields, in particular applied in problems with massive data volume and high efficiency. Experimental outcomes show the robustness of our method.
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