the prediction of surface tension of ternary mixtures at different temperatures using artificial neural networks
نویسندگان
چکیده
in this work, artificial neural network (ann) has been employed to propose a practical model forpredicting the surface tension of multi-component mixtures. in order to develop a reliable modelbased on the ann, a comprehensive experimental data set including 15 ternary liquid mixtures atdifferent temperatures was employed. these systems consist of 777 data points generally containinghydrocarbon components. the ann model has been developed as a function of temperature, criticalproperties, and acentric factor of the mixture according to conventional corresponding-state models.80% of the data points were employed for training ann and the remaining data were utilized fortesting the generated model. the average absolute relative deviations (aard%) of the model for thetraining set, the testing set, and the total data points were obtained 1.69, 1.86, and 1.72 respectively.comparing the results with flory theory, brok-bird equation, and group contribution theory hasproved the high prediction capability of the attained model.
منابع مشابه
The Prediction of Surface Tension of Ternary Mixtures at Different Temperatures Using Artificial Neural Networks
In this work, artificial neural network (ANN) has been employed to propose a practical model for predicting the surface tension of multi-component mixtures. In order to develop a reliable model based on the ANN, a comprehensive experimental data set including 15 ternary liquid mixtures at different temperatures was employed. These systems consist of 777 data points generally containing hydrocar...
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عنوان ژورنال:
iranian journal of oil & gas science and technologyناشر: petroleum university of technology
ISSN 2345-2412
دوره 3
شماره 3 2014
کلمات کلیدی
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