CIESC Journal ›› 2005, Vol. 56 ›› Issue (5): 890-893.
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CHEN Yanze;DING Xinwei;YU Jianliang
Online:
Published:
陈彦泽;丁信伟;喻建良
Abstract: The work address the problem of modeling the dynamical oscillating behavior during both unstable and stable operations, of an experimental thermosyphon. A standard RBF artificial neural network-based prediction model was developed for predicting the oscillating heat transfer of thermosyphon by means of input-output experimental measurements with the characteristics of time series. A comparison of prediction values between the RBF network and the MLP network was giving.The precision of RBF network was higher than that of the other neural networks such as BP-MLP network etc. The dynamical model of RBF network could be used to describe, predict and control the heat transfer process of a thermosyphon or a heat pipe system.
Key words: 重力热管, 径向基神经网络, 振荡传热, 动态模型, 时间序列
关键词: 重力热管, 径向基神经网络, 振荡传热, 动态模型, 时间序列
CHEN Yanze, DING Xinwei, YU Jianliang. Dynamical model of RBF neural network-based prediction for heat transfer oscillating behavior of thermosyphon[J]. CIESC Journal, 2005, 56(5): 890-893.
陈彦泽, 丁信伟, 喻建良. 重力热管振荡传热特性RBF神经网络动态建模 [J]. 化工学报, 2005, 56(5): 890-893.
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