Progress on statistical learning systems as data mining tools for the creation of automatic databases in Fusion environments-Reference-Cited by-同舟云学术

Progress on statistical learning systems as data mining tools for the creation of automatic databases in Fusion environments

Published:2010-07 Issue:3-4 Volume:85 Page:399-402
ISSN:0920-3796
Container-title:Fusion Engineering and Design
language:en
Short-container-title:Fusion Engineering and Design

Author:

Vega J.,Murari A.,Rattá G.A.,González S.,Dormido-Canto S.

Publisher

Elsevier BV

Subject

Mechanical Engineering,General Materials Science,Nuclear Energy and Engineering,Civil and Structural Engineering

Reference8 articles.

1. The spider—A machine learning in Matlab. . Max-Planck Institute for Biological Cybernetics, Tuebingen, Germany. http://www.kyb.tuebingen.mpg.de/bs/people/spider/main.html.

2. Learning From Data;Cherkassky,1998

3. J. Vega, A. Murari, G. Vagliasindi, G.A. Rattá, Automated estimation of L/H transition times at JET by combining Bayesian statistics and support vector machines, Nuclear Fusion 49 (2009) 085023 (11 pp).

4. A.J. Meakins, A study of the L-H transition in tokamak fusion experiments. PhD Thesis, Imperial College, London, UK, 2008.

5. Combining Pattern Classifiers: Methods and Algorithms;Kuncheva,2004

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. An intelligent identification method of the edge coherent mode in EAST;Fusion Engineering and Design;2019-08

2. Overview of TJ-II experiments;Nuclear Fusion;2011-08-31

3. Parallelization of automatic classification systems based on support vector machines: Comparison and application to JET database;Fusion Engineering and Design;2010-07