A novel approach for classification and forecasting of time series in particle accelerators
S Li, M Zacharias, J Snuverink, J Coello de Portugal… - Information, 2021 - mdpi.com
The beam interruptions (interlocks) of particle accelerators, despite being necessary safety
measures, lead to abrupt operational changes and a substantial loss of beam time. A novel
time series classification approach is applied to decrease beam time loss in the High-
Intensity Proton Accelerator complex by forecasting interlock events. The forecasting is
performed through binary classification of windows of multivariate time series. The time
series are transformed into Recurrence Plots which are then classified by a Convolutional …
measures, lead to abrupt operational changes and a substantial loss of beam time. A novel
time series classification approach is applied to decrease beam time loss in the High-
Intensity Proton Accelerator complex by forecasting interlock events. The forecasting is
performed through binary classification of windows of multivariate time series. The time
series are transformed into Recurrence Plots which are then classified by a Convolutional …
[PDF][PDF] A Novel Approach for Classification and Forecasting of Time Series in Particle Accelerators. Information 2021, 12, 121
S Li, M Zacharias, J Snuverink, J Coello de Portugal… - 2021 - infoscience.epfl.ch
The beam interruptions (interlocks) of particle accelerators, despite being necessary safety
measures, lead to abrupt operational changes and a substantial loss of beam time. A novel
time series classification approach is applied to decrease beam time loss in the High-
Intensity Proton Accelerator complex by forecasting interlock events. The forecasting is
performed through binary classification of windows of multivariate time series. The time
series are transformed into Recurrence Plots which are then classified by a Convolutional …
measures, lead to abrupt operational changes and a substantial loss of beam time. A novel
time series classification approach is applied to decrease beam time loss in the High-
Intensity Proton Accelerator complex by forecasting interlock events. The forecasting is
performed through binary classification of windows of multivariate time series. The time
series are transformed into Recurrence Plots which are then classified by a Convolutional …
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