Prediction of enthalpy of fusion of pure compounds using an Artificial Neural Network-Group Contribution method

被引：32
|
作者：
Gharagheizi, Farhad [1 ]
Salehi, Gholam Reza [2 ]
机构：
[1] Saman Energy Giti Co, Tehran, Iran
[2] Islamic Azad Univ, Nowshahr Branch, Nowshahr, Iran
来源：
THERMOCHIMICA ACTA | 2011年 / 521卷 / 1-2期
关键词：
Enthalpy of fusion; Heat of fusion; Group Contribution; Artificial Neural Network; THERMODYNAMIC PROPERTIES; MODELS;
D O I：
10.1016/j.tca.2011.04.001
中图分类号：
O414.1 [热力学];
学科分类号：
摘要：
In this work, the Artificial Neural Network-Group Contribution (ANN-GC) method is applied to estimate the enthalpy of fusion of pure chemical compounds at their normal melting point. 4157 pure compounds from various chemical families are investigated to propose a comprehensive and predictive model. The obtained results show the Squared Correlation Coefficient (R-2) of 0.999, Root Mean Square Error of 0.82 kJ/mol, and average absolute deviation lower than 2.65% for the estimated properties from existing experimental values. (C) 2011 Elsevier B.V. All rights reserved.
引用
收藏
页码：37 / 40
页数：4
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