@article{(Open Science Index):https://publications.waset.org/pdf/71,
	  title     = {Artificial Neural Networks for Classifying Magnetic Measurements in Tokamak Reactors},
	  author    = {A. Greco and  N. Mammone and  F.C. Morabito and  M.Versaci},
	  country	= {},
	  institution	= {},
	  abstract     = {This paper is mainly concerned with the application of a novel technique of data interpretation to the characterization and classification of measurements of plasma columns in Tokamak reactors for nuclear fusion applications. The proposed method exploits several concepts derived from soft computing theory. In particular, Artifical Neural Networks have been exploited to classify magnetic variables useful to determine shape and position of the plasma with a reduced computational complexity. The proposed technique is used to analyze simulated databases of plasma equilibria based on ITER geometry configuration. As well as demonstrating the successful recovery of scalar equilibrium parameters, we show that the technique can yield practical advantages compares with earlier methods.
},
	    journal   = {International Journal of Physical and Mathematical Sciences},
	  volume    = {1},
	  number    = {7},
	  year      = {2007},
	  pages     = {313 - 317},
	  ee        = {https://publications.waset.org/pdf/71},
	  url   	= {https://publications.waset.org/vol/7},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 7, 2007},
	}