Department of PhysicsThe rapid increase of the computing power and the development of the e???cient machine learning techniques in recent days allow us to apply the machine learning to various ???eld of researches. The machine learning techniques become e???ective solutions to the ???elds which are not well described by one integrated theory. The physics for the super cooled glassy liquid system is one such ???eld. The prediction of local dynamics based on the local structural information is longstanding problem in glass physics. The latest researches reveal that the local dynamics is actually predictable by utilizing the support vector machine (SVM) and the local structural information. In this thesis, I reproduce the result of the former researches which utilize the SVM and compare it with the result of the neural network. In addition, I suggest the origin of the dynamic heterogeneity in glassy liquid system. Furthermore, I demonstrate the composition of the local soft regions in glassy liquid systems.clos
