Identification method of key subsequences in continuous casting speed time series based on shapelet
Aiming at the problem of whether there are certain key characteristic shape subsequences in high-frequency time series in industrial control processes and the specific location of this subsequence in the time series,identifica-tion and positioning algorithm for key shape characteristic subsequences in industrial time series is proposed based on shapelet.Shapelet are the most discriminative continuous subsequences in time series.The shapelet set can be ap-plied to the similarity calculation of subsequences of different lengths,and the sequence identification results are in-terpretable.In order to improve the speed and accuracy of identifying and positioning key shape characteristic subse-quences in time series,shapelet sets with specific shape are first extracted and screened from the time series data set based on genetic algorithms.Secondly,the method of data standardization and sliding Euclidean distance is used to calculate the similarity measurement value between the shapelet and the subsequence in the time series,which is used to evaluate the similarity of shape characteristic.Then,the concepts of adaptive similarity threshold and lag time are defined to achieve accurate identification and positioning of characteristic shape subsequences existing in time series and improve the recognition accuracy of key shape subsequences.Finally,the feasibility and accuracy of the method were verified using public standard data sets and time series data of casting speed during continuous casting process.
shapeletgenetic algorithmtime seriessimilarity measurementshape characteristiccontinuous cast-ing process
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