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- W3039695862 abstract "In order to facilitate performance research and control strategy formulation, Elman neural network is used to predict heat transfer coefficient of heat pump, which is convenient for dynamic modeling of PV/t-sahp system. The accuracy of the prediction model was verified by selecting typical sunny and cloudy days. The experimental results show that the maximum relative errors of the predicted values in sunny and cloudy weather are 5.4% and 7.2% respectively. The mean relative errors were 2.57% and 2.69%, respectively. The results show that the prediction model of Elman neural network proposed in this paper is more accurate and can better simulate the actual operation, which can provide technical support for the follow-up research." @default.
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- W3039695862 date "2020-06-01" @default.
- W3039695862 modified "2023-09-25" @default.
- W3039695862 title "Prediction of Heat Transfer Coefficient of PV/T-SAHP Heat Pump System" @default.
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- W3039695862 doi "https://doi.org/10.1088/1742-6596/1549/4/042041" @default.
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