摘要
文中基于BP神经网络方法对冰盘管蓄冷系统的整个蓄冷过程中的蓄冷动态特性参数进行模拟研究,根据实验研究数据对所建的BP神经网络进行网络训练,进而通过预测试验对预测网络进行检验。结果表明:利用BP神经网络方法对整个蓄冷过程中的蓄冷动态特性参数进行模拟的精确度明显高于传统模拟方法,可使研究者更全面、更精确地了解和掌握了蓄冷过程中蓄冷动态特性参数的变化情况,为设计和优化直接蒸发式冰盘管蓄冰系统提供了理论依据。
This paper studied the ice storage dynamic characters of the high density direct evaporation Ice - on - Coil thermal storage process basing on BP neural network. Fistly, trained the BP neural network according to the experiment datas, then forecasted and checked out the training results, which indicated that the BP neural network is available on simulating the ice storage dynamic characters. Accordingly, we can understand and grasp the ice storage dynamic characters more eomprehensive and accurately, and can provide the academic referenee for design and optimization of this series thermal storage air conditioning equipments.
出处
《低温与超导》
CAS
CSCD
北大核心
2007年第1期89-92,共4页
Cryogenics and Superconductivity
基金
河南省科技攻关项目(0524260054)
关键词
直接蒸发
蓄冷动态特性参数
BP神经网络
Direet evaporation, Ice thermal storage dynamic characters, BP neural network