基于Elman型神经网络的空调负荷预测模型

Research on Load Prediction Model of Air Condition System Based on Elman Neural Network

空调系统的负荷与诸多影响因素之间是一种多变量、强耦合、严重非线性的关系 ,且这种关系具有动态性 ,因而传统方法的预测精度不高。而动态回归神经网络能更生动、更直接地反映系统的动态特性。针对这个特点 ,建立了基于Elman型神经网络的空调负荷预测模型 ,并进行了实例预测。文中还比较了Elman网络和BP网络结构的建模效果 ,仿真实验证明了Elman神经网络具有动态特性好、逼近速度快、精度高等特点 ,说明Elman网络是一种新颖、可靠的负荷预测方法。

The load of air condition system is influenced by many factors, and they are variable and nonlinear, The relation between them is dynamic,It is impossible to forecaste the load of air condition syestem accurately by traditional method. But Recurrent Neural Network is able to reflect the dynamic lively and directly. Elman is one of the typical RNN. Based on the analysis as above, prediction model of air-condition system based on Elman neural network is established, and some prediction is done. The prediction accuracy of Elman neural network and BP neural network is compared, and the experiments show that the Elman neural network is efficiency and accuracy , so Elman neural network is a new and reliable method for predicting the load of air-condition system.