基于小波神经网络的干燥后换热研究

Huiming Wei, Xuan Zhang
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引用次数: 0

摘要

小波变换具有表示函数和揭示函数在时频空间联合局部区域的性质的能力。基于小波和人工神经网络,建立了双侧加热条件下垂直狭窄环空上行流动平均干后努塞尔数的小波神经网络预测模型。小波网络模式结合了小波变换的特性和人工神经网络的优点,在解决非线性问题方面具有一定的优势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Study on Post-Dryout Heat Transfer by Using Wavelet Neural Network
Wavelet transformation has the ability of representing a function and revealing the properties of the function in the joint local regions of the time frequency space. Based on wavelet and artificial neural network, a Wavelet Neural Network (WNN) model predicting the average post-dry out Nusselt number for upward flow in vertical narrow annuli with bilateral heating has been developed. The WNN mode combining the properties of the wavelet transform and the advantages of Artificial Neural Networks (ANN) has some advantages of solving non-linear problem.
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