دورية أكاديمية

Stacking of predictors for the automatic classification of disruption types to optimise the control logic

التفاصيل البيبلوغرافية
العنوان: Stacking of predictors for the automatic classification of disruption types to optimise the control logic
المؤلفون: Andrea Murari, Riccardo Rossi, Michele Lungaroni, Matteo Baruzzo, Michela Gelfusa
المساهمون: Murari, A, Rossi, R, Lungaroni, M, Baruzzo, M, Gelfusa, M
بيانات النشر: IOP PUBLISHING LTD
سنة النشر: 2020
المجموعة: Universitá degli Studi di Roma "Tor Vergata": ART - Archivio Istituzionale della Ricerca
مصطلحات موضوعية: disruptions, machine learning predictors, adaptive learning, ensembles of classifiers, transfer learning, de-learning, trajectory learning, stacks of predictors, Settore ING-IND/18 - FISICA DEI REATTORI NUCLEARI
الوصف: Nowadays, disruption predictors, based on machine learning techniques, can perform well but they typically do not provide any information about the type of disruption and cannot predict the time remaining before the current quench. On the other hand, the automatic identification of the disruption type is a crucial aspect required to optimize the remedial actions and a prerequisite to forecasting the time left for intervening. In this work, a stack of machine learning tools is applied to the task of automatic classification of the disruption types. The strategy is implemented from scratch and completely adaptive; the predictors start operating after the first disruption and update their own models, following the evolution of the experimental program, without any human intervention. Moreover, they are designed to implement a form of transfer learning, in the sense that they identify autonomously the most important disruption classes, generating new ones when necessary. The results obtained are very encouraging in terms of both prediction performance and classification accuracy. On the other hand, regarding the narrowing of the warning times, some progress has been achieved, but new techniques will have to be devised to obtain fully satisfactory properties.
نوع الوثيقة: article in journal/newspaper
اللغة: English
العلاقة: info:eu-repo/semantics/altIdentifier/wos/WOS:000619787700001; volume:61; issue:3; journal:NUCLEAR FUSION; https://hdl.handle.net/2108/311065Test; info:eu-repo/semantics/altIdentifier/scopus/2-s2.0-85102169355
DOI: 10.1088/1741-4326/abc9f3
الإتاحة: https://doi.org/10.1088/1741-4326/abc9f3Test
https://hdl.handle.net/2108/311065Test
حقوق: info:eu-repo/semantics/restrictedAccess
رقم الانضمام: edsbas.DC472EC6
قاعدة البيانات: BASE