The QSPR Study for the Net Heat of Combustion of Esters Based on Ant Colony Optimization

Abstract:

A quantitative structure–property relationship (QSPR) model for predicting the standard net heat of combustion () was developed based on the ant colony optimization (ACO) method coupled with the partial least square (PLS) for variable selection. Five molecular descriptors were screened out as the parameters of the model, which were finally constructed using multi-linear regression (MLR) method. A reliable model of five parameters for predicting the of esters was established, which can provide some help for engineering to predict the based on only their molecular structures.

• Periodical: Applied Mechanics and Materials (Volumes 716-717)
• Pages: 180-183
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.716-717.180
• Online since: December 2014
• Authors: Hong Yin Cao*, Rui Wang
• Keywords: Ant Colony Optimization, Ester, Net Heat of Combustion, Prediction, Quantitative Structure-Property Relationship (QSPR)

References

[1] F. Gharagheizi. A Simple Equation for Prediction of Net Heat of Combustion of Pure Chemicals [J]. Chemometrics and Intelligent Laboratory Systems, 2008 (91) 177-180.

DOI: 10.1016/j.chemolab.2007.11.003

[2] F.Y. Hshieh. Predicting Heats of Combustion and Lower Flammability Limits of Organosilicon Compounds [J]. Fire and Materials, 1999 (23) 79-89.

DOI: 10.1002/(sici)1099-1018(199903/04)23:2<79::aid-fam673>3.0.co;2-f

[3] F.Y. Hshieh, D.B. Hirsch, H.D. Beeson. Predicting heats of combustion of polymers using an empirical approach [J]. Fire and Materials, 2003 (27)9-17.

DOI: 10.1002/fam.815

[4] R. L. Cardozo. Prediction of the Enthalpy of Combustion of Organic Compounds [J]. AICHE Journal, 1986 (32) 844-848.

DOI: 10.1002/aic.690320514

[5] W. H. Seaton, B. K. Harrison. A New General Method for Estimation of Heats of Combustion for Hazard Evaluation [J]. Journal of  Loss  Prevention in Process Industry,  1990 (3) 311-320.

DOI: 10.1016/0950-4230(90)80025-6

[6] H.Y. Cao, R. Wang. A New Method for Predicting the Net Heat of Combustion of Organic Compounds [J]. Advanced Materials Research, 2013 (651) 210-215.

DOI: 10.4028/www.scientific.net/amr.651.210

[7] M. Dorigo, L. M. Gambardella. Ant colony system: a cooperative learning approach to the traveling salesman problem [J]. Evolutionary Comput, 1997 (1) 53-66.

DOI: 10.1109/4235.585892

[8] A. Baue, B. Bullnheimer, R. F. Hartl et al. An ant colony optimization approach for the single machine total tardiness problem [C]. CEC 99, Proceedings of the 1999 Congress on Evolutionary Computation, 1999 (2) 1450-1456.

DOI: 10.1109/cec.1999.782653

[9] A. R. M. Silva, G. L. Ramalho. Ant system for the set covering problem Systems [C]. 2001 IEEE International Conference on Man and Cybernetics, 2001 (5) 3129-3133.

DOI: 10.1109/icsmc.2001.971999

[10] W. Q. Xiong, P. Wei. A kind of ant colony algorithm for function optimization [C]. Machine Learning and Cybernetics International Conference on Proceedings, 2002 (1) 552-555.

DOI: 10.1109/icmlc.2002.1176818

[11] W.M. Shi, Q. Shen, W. Kong, et al. QSAR analysis of tyrosine kinase inhibitor using modified ant colonyoptimization and multiple linear regression [J]. European Journal of Medicinal Chemistry, 2007 (42) 81-86.

DOI: 10.1016/j.ejmech.2006.08.001

[12] Project 801. Evaluated Process Design Data, Public Release Documentation, Design Institute for Physical Properties (DIPPR), American Institute of Chemical Engineers (AIChE) (2006).