Artificial Neural Networks for the Prediction of Thermo Physical Properties of Diacetone Alcohol Mixtures


  •  T.R Kubendran    
  •  R. Baskaran    
  •  M. Balakrishna    

Abstract

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 <1%.


This work is licensed under a Creative Commons Attribution 4.0 License.
  • ISSN(Print): 1913-8989
  • ISSN(Online): 1913-8997
  • Started: 2008
  • Frequency: quarterly

Journal Metrics

WJCI (2020): 0.439

Impact Factor 2020 (by WJCI): 0.247

Google Scholar Citations (March 2022): 6907

Google-based Impact Factor (2021): 0.68

h-index (December 2021): 37

i10-index (December 2021): 172

(Click Here to Learn More)

Contact