| 应用神经网络研究CO_2-有机化合物二组分体系的临界温度和临界压力 |
| |
| 引用本文： | 张敬畅,刘慷,曹维良. 应用神经网络研究CO_2-有机化合物二组分体系的临界温度和临界压力[J]. 石油化工, 2003, 32(2): 125-128 |
| |
| 作者姓名： | 张敬畅 刘慷 曹维良 |
| |
| 作者单位： | 北京化工大学理学院,北京,100029 |
| |
| 基金项目： | 国家自然科学基金资助项目(2007604)，国家教育部博士点资助项目(2000001005)。 |
| |
| 摘 要： | 使用Levenberg Marquart算法和人工神经网络技术对文献给出的CO2-乙醇、CO2-丙酮、CO2-甲苯、CO2-丙醇4个二组分体系的临界温度和临界压力数据进行了拟合计算,计算结果与数据较符合,证明了在没有状态方程和混合规则时,经过训练好的神经网络具有研究CO2-有机化合物二组分体系临界温度和临界压力的可行性和准确性,并能够对CO2-有机化合物二组分体系的临界温度和临界压力进行计算和预测。
|
| 关 键 词： | CO2 二组分体系 临界温度 临界压力 神经网络 |
| 文章编号： | 1000-8144(2003)02-0125-04 |
| 修稿时间： | 2002-09-29 |
Application of Artificial Neural Network (ANN)to Investigation of Supercritical Temperature and Pressure of CO2 Binary Systems |
| |
| ZHANG Jing-chang,LIU Kang,CAO Wei-liang. Application of Artificial Neural Network (ANN)to Investigation of Supercritical Temperature and Pressure of CO2 Binary Systems[J]. Petrochemical Technology, 2003, 32(2): 125-128 |
| |
| Authors: | ZHANG Jing-chang LIU Kang CAO Wei-liang |
| |
| Abstract: | Levenberg-Marquart algorithm and artificial neural networks were used to investigate the critical temperatures and critical pressures of four binary systems with supercritical CO 2,such as CO 2- ethanol,CO 2-acetone,CO 2-toluene,and CO 2-propanol.The calculation results meet the experimental data well,which can prove that the trained artificial neural networks has the feasibility and validity in investigating the T Cm and p Cm of binary systems with supercritical CO 2 without employing the equation of state and mixing rules.The trained ANN also can be used to predict the T Cm and p Cm of binary systems with supercritical CO 2 when the second component contents were unknown. |
| |
| Keywords: | carbon dioxide binary systems supercritical temperature supercritical pressure ANN |
| 本文献已被 CNKI 万方数据 等数据库收录！ |
