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

Abstract

Not provided.

Authors:
ORCiD logo [1]; ORCiD logo [1]
  1. Massachusetts Institute of Technology Plasma Science and Fusion Center, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139
Publication Date:
Research Org.:
General Atomics, San Diego, CA (United States); Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States)
Sponsoring Org.:
USDOE Office of Science (SC)
OSTI Identifier:
1540362
DOE Contract Number:  
FC02-04ER54698; SC0014264
Resource Type:
Journal Article
Journal Name:
Fusion Science and Technology
Additional Journal Information:
Journal Volume: 74; Journal Issue: 1-2; Journal ID: ISSN 1536-1055
Publisher:
American Nuclear Society
Country of Publication:
United States
Language:
English
Subject:
Nuclear Science & Technology

Citation Formats

Rea, Cristina, and Granetz, Robert S. Exploratory Machine Learning Studies for Disruption Prediction Using Large Databases on DIII-D. United States: N. p., 2018. Web. doi:10.1080/15361055.2017.1407206.
Rea, Cristina, & Granetz, Robert S. Exploratory Machine Learning Studies for Disruption Prediction Using Large Databases on DIII-D. United States. doi:10.1080/15361055.2017.1407206.
Rea, Cristina, and Granetz, Robert S. Wed . "Exploratory Machine Learning Studies for Disruption Prediction Using Large Databases on DIII-D". United States. doi:10.1080/15361055.2017.1407206.
@article{osti_1540362,
title = {Exploratory Machine Learning Studies for Disruption Prediction Using Large Databases on DIII-D},
author = {Rea, Cristina and Granetz, Robert S.},
abstractNote = {Not provided.},
doi = {10.1080/15361055.2017.1407206},
journal = {Fusion Science and Technology},
issn = {1536-1055},
number = 1-2,
volume = 74,
place = {United States},
year = {2018},
month = {2}
}