Abstract
Applications of neural networks to data analysis and control of fusion plasmas are reviewed. First, a brief introduction to the general features of a neural network is presented, where the neural network is considered as a continuous mapping device, a classification device, a statistical processing device, and a time series predicition device. Then, the applications of neural networks to the research field are explained where the problems to be solved are classified a sfitting function, shaping an experimentally obtained spectrum, analyzing equilibrium quantity, prediction, tomography, and control problems. Throughout the article, we restrict ourselves to description of applications of multi-layer neural networks.
