Abstract In order to effectively mine the structural features in time series and simplify complexity of analysis, equiprobable symbolization pattern entropy (EPSPE) is proposed this paper. The original are implemented through symbolic processing according an equal probability distribution. Then, sliding window technique used obtain a finite number different patterns, pairs determined by calcula...

As companies rely on an ever increasing number of connected devices for their day to operations, a need arises automated anomaly detectors constantly observe crucial device metrics in real time prevent downtime and data loss. production environments tend monitor huge amount these metrics, it prevents current state-of-the-art techniques be deployed as the required computational resources is too ...

The rapid growth of Internet Things (IoT) and sensing technologies has led to an increasing interest in time-series data analysis. In many domains, detecting patterns IoT interpreting these are challenging issues. There several methods analysis that deal with issues such as volume velocity streams. However, analysing the content streams extracting insights from dynamic is still a task. this pap...

in this paper, we propose a new residual analysis method using fourier series transform into fuzzy time series model for improving the forecasting performance. this hybrid model takes advantage of the high predictable power of fuzzy time series model and fourier series transform to fit the estimated residuals into frequency spectra, select the low-frequency terms, filter out high-frequency term...