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  • 标题:Artificial Neural Networks for the Prediction of Thermo Physical Properties of Diacetone Alcohol Mixtures
  • 本地全文:下载
  • 作者:T.R Kubendran ; R. Baskaran ; M. Balakrishna
  • 期刊名称:Computer and Information Science
  • 印刷版ISSN:1913-8989
  • 电子版ISSN:1913-8997
  • 出版年度:2008
  • 卷号:1
  • 期号:4
  • 页码:66
  • DOI:10.5539/cis.v1n4P66
  • 出版社:Canadian Center of Science and Education
  • 摘要:A predictive method based on Artificial networks has been developed for the thermophysical properties of binary liquid mixtures of diacetone alcohol with benzene, chlorobenzene and bromobenzene at (303.15,313.15 and 323.15) K. In method 1, a committee ANN was trained using 5 physical properties combined with absolute temperature as its input to predict thermo physical properties of liquid mixtures. Using these data we found out the predicted data for intermediate mole fraction of different systems without conducting experiments. ANN with back-propagation algorithm is proposed, for Multi-pass Turning Operation and developed in MATLAB. Compared to other prediction techniques, the proposed ANN approach is highly accurate and error is
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