| 基于RBF网络的制冷压缩机热力性能计算 |
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| 引用本文： | 詹涛,张春路,王昔林,丁国良. 基于RBF网络的制冷压缩机热力性能计算[J]. 上海交通大学学报, 2001, 35(8): 1172-1174 |
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| 作者姓名： | 詹涛 张春路 王昔林 丁国良 |
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| 作者单位： | 上海交通大学制冷与低温工程研究所, |
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| 基金项目： | 国家“973”重点基础研究发展规划项目(G2000026309)子课题 |
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| 摘 要： | 在对制冷压缩机的热力性能进行建模和仿真计算时，运用多层感知器网络虽然可以收到较传统热力计算模型更好的效果，但也存在着诸多缺点，通过引径向基函数（RBF）网络替代多层感知器网络，较好地克服了这些缺点，仿真结果表明了该方法的有效性和相对于多层感知器建模方法的优越性。
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| 关 键 词： | 制冷压缩机 热力性能 人工神经网络 径向基函数 热力计算 电功率 |
| 文章编号： | 1006-2467(2001)08-1172-03 |
| 修稿时间： | 2000-06-07 |
Thermodynamic Performance Simulation of Refrigeration Compressors Based on RBF Networks |
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| ZHAN Tao,ZHANG Chun lu,WANG Xi lin,DING Guo liang. Thermodynamic Performance Simulation of Refrigeration Compressors Based on RBF Networks[J]. Journal of Shanghai Jiaotong University, 2001, 35(8): 1172-1174 |
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| Authors: | ZHAN Tao ZHANG Chun lu WANG Xi lin DING Guo liang |
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| Abstract: | Although the application of multilayer perceptron(MLP) to the simulation of thermodynamic performance of refrigeration compressors can produce better results than conventional thermodynamic models, there are still some problems with it. In this work, MLP is substituted by a radial basis function(RBF) network, which solves these problems successfully. The simulation illustrates the effectiveness of the RBF method presented here and its superiority to the MLP method. |
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| Keywords: | refrigeration compressor thermodynamic performance artificial neural network radial basis function(RBF) |
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