Prediction of dynamic air-conditioning load based on artifical neural networks

被引：0
|
作者：
Li, YY [1 ]
Zhang, CZ [1 ]
Yang, JF [1 ]
Tian, Y [1 ]
Jiao, LZ [1 ]
Zeng, SZ [1 ]
机构：
[1] Wuhan Univ Sci & Technol, Dept Bldg Equipment Engn, Wuhan, Hubei, Peoples R China
来源：
ENERGY CONVERSION AND APPLICATION, VOL I AND II | 2001年
关键词：
artificial neural network; dynamic air-condition load; meteorological parameters; predict;
D O I：
暂无
中图分类号：
O414.1 [热力学];
学科分类号：
摘要：
Based on the characteristics of strong-inertia and far time lag and strong coupling, uncertainly nonlinear multi-parameter air-conditioning system is difficult to be described with accurate mathematical model. this paper combines the predictive optimum ideas and the neural networks character, which can accurately describe a nonlinear and uncertain dynamic process and proposes a model that can predict the load by artificial neural networks Using real data and L-M optimized method to train the neural networks and conduct the pseudo-real-time simulation the result indicates that this method is a new and reliable way for predicting the dynamic load efficiently and accurately in real time.
引用
收藏
页码：993 / 996
页数：4
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