摘要
采用神经网络对冬季运行的空气源热泵冷热水机组中螺杆式压缩机的特性进行了模拟。采用误差反向传播算法 (BP算法 )对网络的连接权值进行学习和调整，以满足给定的精度要求。只要训练样本可靠，采用该方法建模可以达到比较高的精度要求。
The performance of screw compressor in air source heat pump heater/chiller unit operating in winter is simulated using the neural networks. In order to satisfy the requirement of the given precision, the connection power of the networks is studied and adjusted using the backpropagation training algorithm (BP algorithm). Modeling with this method can achieve high precision if the training samples are reliable.
出处
《哈尔滨建筑大学学报》
2000年第6期87-91,共5页
Journal of Harbin University of Civil Engineering and Architecture
关键词
神经网络
空间源热泵冷热水机组
压缩机
模拟
neural networks
air source heat pump heater/chiller unit
compressor
training sample
backpropagation training algorithm
