Case study of evaluation of ground source heat pump system based on ANN and ANFS models.
发布时间：2023-04-22
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- 论文类型：
- 文章
- 第一作者：
- 孙苇娟
- 通讯作者：
- 胡平放
- 合写作者：
- 雷飞,朱娜,江章宁
- 发表刊物：
- Applied Thermal Engineering
- 收录刊物：
- SCI
- 所属单位：
- 华中科技大学
- 刊物所在地：
- United Kingdom
- 学科门类：
- 工学
- 一级学科：
- 土木工程
- 项目来源：
- 湖北省科技厅
- 文献类型：
- J
- 卷号：
- 87
- 页面范围：
- 586-594
- ISSN号：
- 1359-4311
- 关键字：
- Artificial neural network;Adaptive neuro-fuzzy inference system; Ground source heat pump; COP
- DOI码：
- 10.1016/j.applthermaleng.2015.04.082
- 发表时间：
- 2015-08-05
- 影响因子：
- 6.465
- 摘要：
- This paper presents case studies with a method to predict the coefficient of performance (COP) of the heat pump and the COPs of ground source heat pump (GSHP) system with limited parameters. The method was based on an artificial neural network (ANN) model and an adaptive neuro-fuzzy inference system (ANFIS) model. Two GSHP systems were monitored respectively to get the training and test data. ANN models with different neurons in the hidden layer were compared according to the statistical validation results, and the models with five neurons in the hidden layer appears to be the best optimal topology for the prediction of COP of the heat pump and COPs of the system. ANFIS with different membership functions (MFs) and various numbers of MFs were compared. Gaussmf with three functions appeared to be the most optimal membership function for the ANFIS model calculating the COP of the heat pump. The optimal ANFIS was the model with two Gaussmf as its member function to predict the COPs of the system. It was found that the models provided high accuracy and reliability for calculating performance indexes of GSHP system.