Modelica-based system simulation and neural network integration method

The invention discloses a system simulation and neural network integration method based on Modelica, and the method comprises the steps: constructing an accurate system simulation model through employing a Modelica language, obtaining key operation data, carrying out the training of the key operation data through a neural network by means of Python, and forming a concise and efficient proxy model which can accurately reflect an actual system operation state. According to the method, the function that the agent model can be directly used for rapidly evaluating the system is achieved, direct dependence on a complex Modelica model is reduced, the calculation efficiency is improved, and especially in a scene needing frequent operation or rapid evaluation, an accurate and efficient system simulation and analysis method is provided; the method has important practical application value in the aspects of engineering design, system optimization, decision support and the like. 本发明公开了一种基于Modelica的系统仿真与神经网络集成方法，通过运用Model