关键词: 时间序列, 循环神经网络, 长短时记忆网络, tensorflow, 热力站建模

Abstract: Aiming at the problem about the heating station control system belongs to multivariable, nonlinear, strong coupling and large time delay complex process control system, it is difficult to establish an accurate model. The long short-term memory based on recurrent neural network is proposed to model the heating station control system. The algorithm not only considers the influence factors in time factor, but also solves the problem of long sequence information loss. Using a large real-time data in Baotou heating station, the neural network model is build by the tensorflow framework. The simulation result shows that the long short-term memory network modeling can effectively reduce the modeling error, and improve the accuracy of neural network modeling system in heating station.

Key words: time series, recurrent neural network, long short-term memory, tensorflow, modeling of heating station