| 基于RBF网络的冷却塔运行特性数学模型 |
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| 引用本文： | 李勇,黄启虎. 基于RBF网络的冷却塔运行特性数学模型[J]. 汽轮机技术, 2002, 44(1): 5-7 |
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| 作者姓名： | 李勇 黄启虎 |
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| 作者单位： | 东北电力学院动力系,吉林市,132012;辽宁发电厂,抚顺,113000 |
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| 摘 要： | 双现有的冷却塔运行性能评价方法进行了综述,指出其各自存在的问题。采用人工神经网络中相对成熟的RBF网络建立了冷却塔特性的数学模型,并与常规的线性和非线性模型进行了比较,结果表明采用RBF网络能更准确地反映冷却塔的性能。为评价冷却塔运行性能,提供了一种更准确、更简单的方法。
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| 关 键 词： | 冷却塔 运行性能 RBF网络 评价 |
| 文章编号： | 1001-5884(2002)01-0005-03 |
| 修稿时间： | 2001-08-09 |
Mathematics Model of Cooling Tower Operation Performance Based on RBF Neural Networks |
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| LI Yong ,HUANG Qi hu. Mathematics Model of Cooling Tower Operation Performance Based on RBF Neural Networks[J]. Turbine Technology, 2002, 44(1): 5-7 |
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| Authors: | LI Yong HUANG Qi hu |
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| Affiliation: | LI Yong 1,HUANG Qi hu 2 |
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| Abstract: | A brief description is given of existing appraising methods for the performance of cooling tower and their shortcoming firstly. Then the mathematics model of cooling tower operation performance is given by means of the relative perfect RBF neural networks. Comparing with the usual linearity and non-linearity cooling tower mathematics model, the RBF neural networks mathematics model can more truly reflect cooling tower operation performance. This conclusion is valuable for giving a more true and simple method for appraising the operation performance of cooling tower. |
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| Keywords: | cooling tower operation performance RBF neural networks |
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