Synthetic data generation using generative adversarial network for tokamak plasma current quench experiments

Disruption prediction at JET through Deep Convolutional Neural Networks using spatiotemporal information from plasma profiles

(2022) Enrico Aymerich et al.   NUCLEAR FUSION

Prospects for Disruption Handling in a Tokamak-Based Fusion Reactor

(2021) N. W. Eidietis   FUSION SCIENCE AND TECHNOLOGY

Real-time prediction of high density EAST disruptions using Random Forest

(2021) Wenhui Hu et al.   NUCLEAR FUSION

An Application of Machine Learning for Plasma Current Quench Studies via Synthetic Data Generation

(2021) Niharika Dalsania et al.   FUSION ENGINEERING AND DESIGN

Progress Toward Interpretable Machine Learning-Based Disruption Predictors Across Tokamaks

(2020) C. Rea et al.   FUSION SCIENCE AND TECHNOLOGY

Characterization of the plasma current quench during disruptions in ADITYA tokamak

(2020) Shishir Purohit et al.   NUCLEAR FUSION

Disruption prediction using a full convolutional neural network on EAST

(2020) B H Guo et al.   PLASMA PHYSICS AND CONTROLLED FUSION

Predicting disruptive instabilities in controlled fusion plasmas through deep learning

(2019) Julian Kates-Harbeck et al.   NATURE

Machine learning for disruption warning on Alcator C-Mod, DIII-D, and EAST

(2019) Kevin Joseph Montes et al.   NUCLEAR FUSION

A disruption predictor based on a 1.5-dimensional convolutional neural network in HL-2A

(2019) Zongyu Yang et al.   NUCLEAR FUSION

Deep Learning for Plasma Tomography and Disruption Prediction From Bolometer Data

(2019) Diogo R. Ferreira et al.   IEEE TRANSACTIONS ON PLASMA SCIENCE

Exploratory Machine Learning Studies for Disruption Prediction Using Large Databases on DIII-D

(2018) Cristina Rea et al.   FUSION SCIENCE AND TECHNOLOGY

Disruption prediction investigations using Machine Learning tools on DIII-D and Alcator C-Mod

(2018) C Rea et al.   PLASMA PHYSICS AND CONTROLLED FUSION

Deep Gaussian mixture models

(2017) Cinzia Viroli et al.   STATISTICS AND COMPUTING

Prediction of density limit disruptions on the J-TEXT tokamak

(2016) S Y Wang et al.   PLASMA PHYSICS AND CONTROLLED FUSION

Analysis of Similarity Measures in Times Series Clustering for the Discovery of Building Energy Patterns

(2013) Félix Iglesias et al.   Energies

Characteristics of current quenches during disruptions in the J-TEXT tokamak

(2012) Y Zhang et al.   PHYSICA SCRIPTA

Theory of tokamak disruptions

(2012) Allen H. Boozer   PHYSICS OF PLASMAS

Study of current decay time during disruption in JT-60U tokamak

(2010) Y. Shibata et al.   NUCLEAR FUSION

Characterization of the plasma current quench during disruptions in the National Spherical Torus Experiment

(2009) S.P. Gerhardt et al.   NUCLEAR FUSION