Search Results - "Cannas, B."

Improvements in disruption prediction at ASDEX Upgrade by Aledda, R., Cannas, B., Fanni, A., Pau, A., Sias, G.

“…•A disruption prediction system for AUG, based on a logistic model, is designed.•The length of the disruptive phase is set for each disruption in the training…”
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Towards an automatic filament detector with a Faster R-CNN on MAST-U by Cannas, B., Carcangiu, S., Fanni, A., Farley, T., Militello, F., Montisci, A., Pisano, F., Sias, G., Walkden, N.

“…In the present magnetically confined plasmas, the prediction of particle loading on material surfaces is a primary concern in view of the protection of plasma…”
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eXplainable artificial intelligence applied to algorithms for disruption prediction in tokamak devices by Bonalumi, L., Aymerich, E., Alessi, E., Cannas, B., Fanni, A., Lazzaro, E., Nowak, S., Pisano, F., Sias, G., Sozzi, C.

“…Introduction: This work explores the use of eXplainable artificial intelligence (XAI) to analyze a convolutional neural network (CNN) trained for disruption…”
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Physics Informed Neural Networks towards the real-time calculation of heat fluxes at W7-X by Aymerich, E., Pisano, F., Cannas, B., Sias, G., Fanni, A., Gao, Y., Böckenhoff, D., Jakubowski, M.

“…•Monitoring the heat flux in real-time is pivotal for steady-state fusion operation.•Existing 2D codes for heat flux estimation, such as THEODOR, are only…”
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Disruption prediction with adaptive neural networks for ASDEX Upgrade by Cannas, B., Fanni, A., Pautasso, G., Sias, G.

“…In this paper, an adaptive neural system has been built to predict the risk of disruption at ASDEX Upgrade. The system contains a Self Organizing Map, which…”
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Disruption Prediction Approaches Using Machine Learning Tools in Tokamaks by Sias, G., Cannas, B., Carcangiu, S., Fanni, A., Murari, A., Pau, A., Contributors, Jet

“…Nuclear fusion is one of the best options to achieve a virtually limitless energy source in the future. However, sustaining burning plasma reactions is very…”
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Multivariate statistical models for disruption prediction at ASDEX Upgrade by Aledda, R., Cannas, B., Fanni, A., Sias, G., Pautasso, G.

“…In this paper, a disruption prediction system for ASDEX Upgrade has been proposed that does not require disruption terminated experiments to be implemented…”
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Initial results from the hotspot detection scheme for protection of plasma facing components in Wendelstein 7-X by Ali, A., Niemann, H., Jakubowski, M., Pedersen, T. Sunn, Neu, R., Corre, Y., Drewelow, P., Sitjes, A. Puig, Wurden, G., Pisano, F., Cannas, B., Gao, Y., Ślęczka, M.

“…•We present automatic, near real-time detection of hot spots and identification of surface layers on W7-X test divertor.•Events such as surface layers due to…”
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Algorithms for the Automatic Identification of MARFEs and UFOs in JET Database of Visible Camera Videos by Murari, A, Camplani, M, Cannas, B, Mazon, D, Delaunay, F, Usai, P, Delmond, J F

“…MARFE instabilities and UFOs leave clear signatures in JET fast visible camera videos. Given the potential harmful consequences of these events, particularly…”
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River flow forecast for reservoir management through neural networks by Baratti, R., Cannas, B., Fanni, A., Pintus, M., Sechi, G.M., Toreno, N.

“…River flow forecasts are required to provide basic information for reservoir management in a multipurpose water system optimisation framework. An accurate…”
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Mapping of the ASDEX Upgrade Operational Space for Disruption Prediction by Aledda, R., Cannas, B., Fanni, A., Sias, G., Pautasso, G.

“…The mapping of the n -dimensional plasma parameter space of ASDEX Upgrade (AUG) has been performed using a 2-D self-organizing map (SOM), which reveals the map…”
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Tracking of the plasma states in a nuclear fusion device using SOMs by Camplani, M., Cannas, B., Fanni, A., Pautasso, G., Sias, G.

“…Knowledge discovery consists of finding new knowledge from databases where dimension, complexity, or amount of data is prohibitively large for human…”
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Support vector machines for disruption prediction and novelty detection at JET by Cannas, B., Delogu, R.S., Fanni, A., Sonato, P., Zedda, M.K.

“…In the last years there has been a growing interest on black box approaches to disruption prediction. The drawback of these approaches is that the system could…”
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Criteria and algorithms for constructing reliable databases for statistical analysis of disruptions at ASDEX Upgrade by Cannas, B., Fanni, A., Pautasso, G., Sias, G., Sonato, P.

“…The present understanding of disruption physics has not gone so far as to provide a mathematical model describing the onset of this instability. A disruption…”
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Neural reconstruction of Lorenz attractors by an observable by Cannas, B., Cincotti, S.

“…In this paper, Locally Recurrent Neural Networks (LRNNs) are used to learn the chaotic trajectory of the Lorenz system starting from measurements of an…”
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A generalization of a piece-wise linear circuit model of hysteresis by Cannas, B., Cincotti, S., Daneri, I.

“…A generalization of a piece-wise linear (PWL) circuit model of hysteresis is presented. The model is defined as superposition of hysteresis operators…”
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Higher order reversal hysteresis curves approximation by a piecewise linear circuit model of hysteresis by Cannas, B., Cincotti, S.

“…The approximation properties of higher order reversal hysteresis curves by means of a piecewise linear (PWL) circuit model of hysteresis are studied. The model…”
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MHD spectrogram contribution to disruption prediction using Convolutional Neural Networks by Aymerich, E., Sias, G., Atzeni, S., Pisano, F., Cannas, B., Fanni, A.

“…•A disruption prediction system for JET, based on a Convolutional Neural Network, is designed.•The contribution of the Mirnov coil measurement spectrogram to…”
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CNN disruption predictor at JET: Early versus late data fusion approach by Aymerich, E., Sias, G., Pisano, F., Cannas, B., Fanni, A., the-JET-Contributors

“…This work focuses on the development of a data driven model, based on Convolutional Neural Networks (CNNs), for the real-time detection of disruptive events at…”
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An algebraic observability approach to chaos synchronization by sliding differentiators by Cannas, B., Cincotti, S., Usai, E.

“…In this paper, an observability approach to the synchronization of chaotic and hyperchaotic systems is presented. The proposed method allows the reconstruction…”
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