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Found 3 papers, 1 papers with code
Evaluation of k-means time series clustering based on z-normalization and NP-Free
By systematically investigating the performance of k-means time series clustering with these two normalization techniques, this paper addresses the current gap in k-means time series clustering evaluation and contributes valuable insights to the development of time series clustering.
NP-Free: A Real-Time Normalization-free and Parameter-tuning-free Representation Approach for Open-ended Time Series
Without needing to use any normalization method or tune any parameter, NP-Free can generate a representation for a raw time series on the fly by converting each data point of the time series into a root-mean-square error (RMSE) value based on Long Short-Term Memory (LSTM) and a Look-Back and Predict-Forward strategy.
Coverage Analysis of Net Inscriptions in Coloured Petri Net Models
The contribution of this paper is an approach that establishes a link between coverage analysis known from programming languages and net inscriptions of CPN models.
Software Engineering
