| 引用本文： |
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韦藤幼,黄瑞华.用神经网络预测饱和液体密度[J].广西科学,2000,7(3):201-202,205. [点击复制]
- Wei Tengyou,Huang Ruihua.Using Neural Network to Predict the Density of Saturated Liquid[J].Guangxi Sciences,2000,7(3):201-202,205. [点击复制]
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| 摘要: |
| 使用前向神经网络,采用带阻尼的牛顿二阶学习方法,学习纯物质的饱和液体密度与温度的关系,在熔点到临界点的温度范围内,预测平均误差小于0.03%。适宜的网络工作区间[amin,amax]为[0.5,0.7]。 |
| 关键词: 神经网络 液体密度 预测 牛顿二阶学习方法 |
| DOI： |
| 投稿时间：1999-11-05 |
| 基金项目: |
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| Using Neural Network to Predict the Density of Saturated Liquid |
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Wei Tengyou, Huang Ruihua
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| (The Industrial Testing Experiment Centre, Guangxi University, Xixiangtanglu, Nanning, Guangxi, 530004, China) |
| Abstract: |
| The feed-forword neural network is used to study the relationship between the density of the pure saturated liquid matters and the temperature. The weighs of the neural network are updated by using the damped Newton second order method. The estimated average errors are less than 0.03% between the melting point and the critical point. The suitable working range[amin,amax] is[0.5,0.7] for the network. |
| Key words: neural network density of liquid estimation Newton second order method |
