Modelling of a vertical ground coupled heat pump system by using artificial neural networks

作者: Hikmet Esen , Mustafa Inalli

DOI: 10.1016/J.ESWA.2009.01.055

关键词: Materials scienceHeat exchangerConjugate gradient methodControl theoryHeat pumpSystem identificationArtificial neural networkSigmoid transfer functionSystems modelingTangent

摘要: This paper describes the applicability of artificial neural networks (ANNs) to estimate performance a vertical ground coupled heat pump (VGCHP) system used for cooling and heating purposes experimentally. The involved three exchangers in different depths at 30 (VB1), 60 (VB2) 90 (VB3)m. experimental results were obtained seasons 2006-2007. ANNs have been varied applications they shown be particularly useful modeling identification. In this study, back-propagation learning algorithm with variants, namely Levenberg-Marguardt (LM), Pola-Ribiere conjugate gradient (CGP), scaled (SCG), tangent sigmoid transfer function network so that best approach could found. most suitable neuron number hidden layer found as LM 8 neurons both modes.

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