Development of a neural network technique for KSTAR Thomson scattering diagnostics

作者：Lee Seung Hun^*; Lee J H; Yamada I; Park Jae Sun

来源：Review of Scientific Instruments, 2016, 87(11): 11E533.

DOI：10.1063/1.4961079

Neural networks provide powerful approaches of dealing with nonlinear data and have been successfully applied to fusion plasma diagnostics and control systems. Controlling tokamak plasmas in real time is essential to measure the plasma parameters in situ. However, the chi(2) method traditionally used in Thomson scattering diagnostics hampers real-time measurement due to the complexity of the calculations involved. In this study, we applied a neural network approach to Thomson scattering diagnostics in order to calculate the electron temperature, comparing the results to those obtained with the chi(2) method. The best results were obtained for 10(3) training cycles and eight nodes in the hidden layer. Our neural network approach shows good agreement with the chi(2) method and performs the calculation twenty times faster. Published by AIP Publishing.

• 出版日期2016-11