A back-propagation neural network can easily predict the energy consumption of a pipeline system with fewer mathematical statistics than other methods and a simple pretreatment of the original data.The energy consumption prediction uses different nonlinear influence factors by learning the operation data of a certain pipeline via the BP neural network. Calculated results show a prediction error within 5%, capable of satisfying engineering demand.No uniform selection criterion exists for the number of nodes in the latent layer. The selection of a latent layer and its number of nodes, however, do influence the degree of nonlinear error and therefore need further study.The prediction uses ac...