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Machine learning based automated identification of thunderstorms from anemometric records using shapelet transform
In this context, the use of Shapelet transform is proposed to identify key individual attributes distinctive to extreme wind events based on similarity of shape of their time series.
Data Anomaly Detection for Structural Health Monitoring of Bridges using Shapelet Transform
The shapelet transform is a unique time series representation that is solely based on the shape of the time series data.
Applications of shapelet transform to time series classification of earthquake, wind and wave data
In consideration of the individual attributes distinctive to time series signals in earthquake, wind and ocean engineering, the application of this transform yields a new shape-based feature representation.
Shapelets for earthquake detection
This paper introduces EQShapelets (EarthQuake Shapelets) a time-series shape-based approach embedded in machine learning to autonomously detect earthquakes.
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