volume 46, issue 7, P699-708 2006
DOI: 10.1088/0029-5515/46/7/002
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Abstract: In this paper, different pattern recognition techniques have been tested in order to implement an automatic tool for disruption classification in a tokamak experiment. The considered methods refer to clustering and classification techniques. In particular, the investigated clustering techniques are Self-Organizing Maps and K-means, while classification techniques are Multi-Layer Perceptrons, Support Vector Machines, and k-Nearest Neighbours. Training and testing data have been collected selecting suitable diag…

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