期刊
APPLIED THERMAL ENGINEERING
卷 21, 期 9, 页码 941-953出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/S1359-4311(00)00093-4
关键词
chiller; model; neural network; radial basis function; dynamic
This paper presents a new approach to modelling dynamic processes of vapour-compression liquid refrigeration systems. Using a dynamic neural network model for the performance prediction has been proposed. The model uses a generalised radial basis function neural network as inputs require only those parameters that are easily measurable. It then predicts relevant performance parameters such as the coefficient of performance or compressor work input. It was applied to two different dynamic processes of two different chillers and was found to be able to identify all process characteristics. (C) 2001 Elsevier Science Ltd. All rights reserved.
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