Národní úložiště šedé literatury Nalezeno 2 záznamů.  Hledání trvalo 0.01 vteřin. 
Anomaly Detection in Generated Incident Ticket Volumes
Šurina, Timotej ; Rychlý, Marek (oponent) ; Trchalík, Roman (vedoucí práce)
This bachelor thesis deals with the issue of time series anomaly detection. It presents methods STL decomposition, ARIMA, Exponential Smoothing and LSTM Networks. The aim is to use these methods to create an algorithm that can analyze the trend in a volume of generated incident tickets and detect anomalies form the trend. The solution was created based on a dataset provided by firm AT&T Global Network Services Czech Republic s.r.o. and implemented in the Python programming language.
Anomaly Detection in Generated Incident Ticket Volumes
Šurina, Timotej ; Rychlý, Marek (oponent) ; Trchalík, Roman (vedoucí práce)
This bachelor thesis deals with the issue of time series anomaly detection. It presents methods STL decomposition, ARIMA, Exponential Smoothing and LSTM Networks. The aim is to use these methods to create an algorithm that can analyze the trend in a volume of generated incident tickets and detect anomalies form the trend. The solution was created based on a dataset provided by firm AT&T Global Network Services Czech Republic s.r.o. and implemented in the Python programming language.

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