Hybrid method to predict melting points of organic compounds using group contribution + neural network + particle swarm algorithm

Industrial and Engineering Chemistry Research

Volumn 48, Issue 18, 2009, Pages 8760-8766

  Lazzús, Juan A ^a  

^a DEPARTAMENTO DE BIOLOGÍA   (Chile)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL NEURAL NETWORK; AVERAGE ABSOLUTE RELATIVE DEVIATIONS; EXPERIMENTAL DATA; GROUP CONTRIBUTIONS; HYBRID METHOD; PARTICLE SWARM ALGORITHM; SIMPLE GROUPS;

BACKPROPAGATION; HYBRID SENSORS; MATLAB; MELTING POINT; NEURAL NETWORKS; ORGANIC COMPOUNDS; STEELMAKING;

PARTICLE SWARM OPTIMIZATION (PSO);

EID: 70349329808     PISSN: 08885885     EISSN: None     Source Type: Journal    
DOI: 10.1021/ie900431f     Document Type: Article

References (24)

1. Dearden, J. C. Quantitative-Structure Property Relationships for Prediction of Boiling Point, Vapor Pressure, and Melting Point. Environ. Toxicol. Chem. 2003, 22, 1696-1709.
2. Lazzús, J. A. Neural Network Based on Quantum Chemistry for Predicting Melting Point of Organic Compounds. Chin. J. Chem. Phys. 2009, 22, 19-26.
3. Zhao, L.; Yalkowsky, S. H. A Combined Group Contribution and Molecular Geometry Approach for Predicting Melting Points of Aliphatic Compounds. Ind. Eng. Chem. Res. 1999, 38, 3581-3584.
4. Jain, A.; Yang, G.; Yalkowsky, S. H. Estimation of Melting Points of Organic Compounds. Ind. Eng. Chem. Res. 2004, 43, 7618-7621. (Pubitemid 39482837)
5. Poling, B.; Prausnitz, J. M.; O'Conell, J. P. The Properties of Gases and Liquids; The McGraw-Hill Companies Inc.: New York, 2004.
6. Joback, K.; Reid, R. Estimation of Pure Component Properties from Group Contribution. Chem. Eng. Commun. 1987, 57, 233-243.
7. Lydersen, A. L. Estimation of Critical Properties of Organic Compounds. Report 3; College of Engineering, University of Wisconsin: Madison, WI, 1955.
8. Constantinou, L.; Gani, R. A New Group Contribution Method for the Estimation of Properties of Pure Compounds. AIChE J. 1994, 40, 1697- 1710.
9. Simamora, P.; Yalkowsky, S. H. Group Contribution Methods for Predicting the Melting Points and Boiling Points of Aromatic Compounds. Ind. Eng. Chem. Res. 1994, 33, 1405-1409.
10. Krzyzaniak, J. F.; Myrdal, P. B.; Simamora, P.; Yalkowsky, S. H. Boiling Point and Melting Point Prediction for Aliphatic non-Hydrogen- Bonding Compounds. Ind. Eng. Chem. Eng. 1995, 34, 2530-2535.
11. Tu, C.-H.; Wu, Y.-S. Group-Contribution Estimation of Normal Freezing Points of Organic Compounds. J. Chin. Inst. Chem. Eng. 1996, 27, 323-328.
12. Marrero, J.; Gani, R. Group Contribution Based Estimation of Pure Component Properties. Fluid Phase Equilib. 2001, 183, 183-208.
13. Skander, N.; Chitour, C. E. A New Group-Contribution Method for the Estimation of Physical Properties of Hydrocarbons. Oil Gas Sci. Technol. 2002, 4, 369-376.
14. Wen, X.; Qiang, Y. A New Group Contribution Method for Estimationg Melting and Boiling Points of Organic Compounds. Chem. Eng. Commun. 2004, 191, 75-86.
15. Li, H.; Higashi, H.; Tamura, K. Estimation of Boiling and Melting Points of Light, Heavy and Complex Hydrocarbons by Means of a Modified Group Vector Space Method. Fluid Phase Equilib. 2006, 239, 213-222.
16. Lazzús, J. A. F-T-P Prediction for Ionic Liquids using Neural Networks. J. Taiwan Inst. Chem. Eng. 2009, 40, 213-232.
17. Taskinen, J.; Yliruusi, J. Prediction of Physicochemical Properties Based on Neural Network Modelling. Adv. Drug Deliver. Rev. 2003, 55, 1163-1183.
18. Luo, Q.; Yi, D. A Co-evolving Framework for Robust Particle Swarm Optimization. Appl. Math. Comput. 2008, 199, 611-622.
19. MatLab, version 6.5.0; The MathWorks Inc.: Natick, MA, 2002.
20. Lazzús, J. A. Prediction of Solid Vapor Pressures for Organic and Inorganic Compounds Using a Neural Network. Thermochim. Acta 2009, 489, 53-62.
21. Lazzús, J. A. Estimation of Density as a Function of Temperature and Pressure for Imidazolium-based Ionic Liquids Using a Multilayer Net with Particle Swarm Optimization. Int. J. Thermophys. 2009, 30, 883-909.
22. Da, Y.; Xiurun, G. An Improved PSO-Based ANN with Simulated Annealing Technique. Neurocomputing 2005, 63, 527-533.
23. Jiang, Y.; Hu, T.; Huang, C.; Wu, X. An Improved Particle Swarm Optimization Algorithm. Appl. Math. Comput. 2007, 193, 231-239. (Pubitemid 47562556)
24. Daubert, T. E.; Danner, R. P.; Sibul, H. M.; Stebbins, C. C. Physical and Thermodynamic Properties of Pure Chemicals. Data Compilation; Taylor & Francis: London, 2000.