基于神经网络和过程机理的热流体系统仿真

SIMULATION OF THERMOFLUID SYSTEM BASED ON NEURAL NETWORK AND PROCESS MECHANISM

构建了一种基于复合神经网络和过程机理特性的热流体系统仿真模型 .该模型在形式上为一种复合人工神经网络模型 ,保证了模型具有十分理想的仿真速度 ;在网络模型设计上较好地考虑了系统输入与输出间的物理基础 ,网络模型在一定程度上由常规的黑箱模型转化为“灰箱模型” ,网络的训练除了具有常规的输入、输出间的纯数值映射关系学习功能之外较好地体现了对象输入与输出间的物理机理学习 ,保证了网络模型具有良好的联想能力、外推能力和时间递推能力 .

This paper presents a simulation model of a thermofluid system, which is based on combined neural network and process mechanism characteristics. It is an artificial neural network model, the ideal simulation speed thus is ensured. During design of the network model, the physical fundamental with which the system between input and output is considered. This network model is a grey box rather than a conventional black box to a certain degree. Besides the conventional learning function of numerical mapping between input and output, training of the network reflects the learning of physical mechanism between input and output, thereby associative ability, extending inference ability and recurrent ability of the network model are ensured..