Configuration design of the trainset of a high-speed train using neural networks

Prediction of the top(service) speeds of high-speed trains and configuration design to trainset of them has been studied using the neural network system The traction system. The traction system of high-speed trains is composed of transformers, motor blocks, and traction motors of which locations and number in the trainset formation should be determine in the early stage of train conceptural design. Components of the traction system are the heaviest parts in a train so that it gives strong influence to the top speeds of high-speed trains. Prediction of the top speeds has been performed mainly with data associated with the traction system based on the frequently used neural network system-backpropagation. The neural network has been trained with the data of the high-speed trains such as TGV, ICE, and Shinkanse. Configuration design of the trainset determines the number of trains motor cars, traction motors, weights and power of trains. Configuration results from the neural network are more accurate if neural networks is trained with data of the same type of trains will be designed.