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The Prediction of Surface Tension of Ternary Mixtures At Different Temperatures Using Artificial Neural Networks
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نویسنده
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Khazaei Ali ,Parhizgar Hossein ,Dehghani Mohammad Reza
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منبع
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Iranian Journal Of Oil And Gas Science And Technology - 2014 - دوره : 3 - شماره : 3 - صفحه:47 -61
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چکیده
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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.
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کلیدواژه
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Surface Tension ,Mixtures ,Artificial Neural Network
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آدرس
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Iran University Of Science And Technology, Thermodynamics Research Laboratory, School Of Chemical Engineering, Iran University Of Science & Technology, Tehran, Iran, ایران, Islamic Azad University, Young Researchers And Elites Club, Marvdasht Branch, Islamic Azad University, Marvdasht, Iran, ایران, Iran University Of Science And Technology, Thermodynamics Research Laboratory, School Of Chemical Engineering, Iran University Of Science & Technology, Tehran, Iran, ایران
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Authors
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