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Study on Non Energy Saving Status Detection of Groundwater Heat Pump System Using Artificial Neural Network Method

机译:使用人工神经网络方法研究地下水热泵系统的非节能现状检测

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Presents two types of characteristic data: basic characteristic parameters and index characteristic parameters for non energy saving status detection (NESSD) of groundwater heat pump (GWHP) system, establishes the relationship database between characteristic data and fault factors of NESSD. For three kinds of improving back propagation (BP) algorithms: Variable Learning Rate (VLR) BP algorithm, Scaled Conjugate Gradient (SCG) BP algorithm, and Levenberg-Marquardt (LM) BP algorithm, these various algorithms' comparative study had been conducted on the GWHP system's NESSD. The optimal algorithm among them is determined and the GWHP system's NESSD as cases studies can be carried out based on the most suitable BP algorithm.
机译:呈现两种类型的特征数据:用于地下水热泵(GWHP)系统的非节能状态检测(NESSD)的基本特征参数和索引特性参数,在NESSD的特征数据和故障因素之间建立关系数据库。对于三种改进的反向传播(BP)算法:可变学习率(VLR)BP算法,缩放共轭梯度(SCG)BP算法,以及Levenberg-Marquardt(LM)BP算法,这些算法已经进行了对比研究GWHP系统的NESSD。确定它们中的最佳算法,并且可以基于最合适的BP算法执行GWHP系统的NESSD作为病例研究。

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