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Determination of Parachor of Various Compounds Using an Artificial Neural Network␣Group Contribution Method

Abstract : In this communication, an Artificial Neural Network␣Group Contribution algorithm is applied to represent/predict the parachor of pure chemical compounds. To propose a reliable and predictive tool, 227 pure chemical compounds are investigated. Using the developed method, we obtain satisfactory results that are quantified by the following statistical parameters: absolute average deviations of the represented/predicted parachor values from existing experimental ones, %AAD = 1.2%; and squared correlation coefficient, R2 = 0.997.
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https://hal-mines-paristech.archives-ouvertes.fr/hal-00595557
Contributor : Bibliothèque Mines Paristech <>
Submitted on : Wednesday, May 25, 2011 - 10:14:58 AM
Last modification on : Thursday, September 24, 2020 - 5:22:04 PM

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Farhad Gharagheizi, Ali Eslamimanesh, Amir H. Mohammadi, Dominique Richon. Determination of Parachor of Various Compounds Using an Artificial Neural Network␣Group Contribution Method. Industrial and engineering chemistry, American Chemical Society (ACS), 2011, 50 (9), pp.5815-5823. ⟨10.1021/ie102464t⟩. ⟨hal-00595557⟩

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