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مقاله Neural Network Approach for Prediction of Asphaltene precipitation and comparison it with FloryدرHuggins model in crude oil با word دارای 8 صفحه می باشد و دارای تنظیمات در microsoft word می باشد و آماده پرینت یا چاپ است

فایل ورد مقاله Neural Network Approach for Prediction of Asphaltene precipitation and comparison it with FloryدرHuggins model in crude oil با word کاملا فرمت بندی و تنظیم شده در استاندارد دانشگاه و مراکز دولتی می باشد.

این پروژه توسط مرکز مرکز پروژه های دانشجویی آماده و تنظیم شده است

توجه : در صورت  مشاهده  بهم ریختگی احتمالی در متون زیر ،دلیل ان کپی کردن این مطالب از داخل فایل ورد می باشد و در فایل اصلی مقاله Neural Network Approach for Prediction of Asphaltene precipitation and comparison it with FloryدرHuggins model in crude oil با word،به هیچ وجه بهم ریختگی وجود ندارد

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بخشی از متن مقاله Neural Network Approach for Prediction of Asphaltene precipitation and comparison it with FloryدرHuggins model in crude oil با word :

سال انتشار: 1386

محل انتشار: پنجمین کنگره بین المللی مهندسی شیمی

تعداد صفحات: 8

چکیده:

Asphaltenes are problematic substances for heavy-oil upgrading processes. Deposition of complex and heavy organic compounds, which exist in petroleum crude oil, can cause a lot of problems. In this work an Artificial Neural Networks (ANN) approach for estimation of asphaltene precipitation has been proposed. Among the various training algorithms, the ANN, Radial Basis (RBF) method had the best prediction performance and was used for prediction of the asphaltene precipitation. The experimental data of two samples typical crude oil were pre-scaled and used for training of Artificial Neural Networks. The ANN has been trained with 2/3 of data set and 1/3 of samples have been used for testing the predictions of NN. The results show ANN capability to predict the measured data. ANN model performance is also compared with Flory-Huggins model. The comparison confirms the superiority of the ANN model.

 

 

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