فایل ورد مقالات

 

مقاله Prediction of wax precipitation by intelligent methods and comparison with Multisolid model in crude oil systems دارای 6 صفحه می باشد و دارای تنظیمات در microsoft word می باشد و آماده پرینت یا چاپ است

فایل ورد مقاله Prediction of wax precipitation by intelligent methods and comparison with Multisolid model in crude oil systems 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 Prediction of wax precipitation by intelligent methods and comparison with Multisolid model in crude oil systems،به هیچ وجه بهم ریختگی وجود ندارد

---

بخشی از متن مقاله Prediction of wax precipitation by intelligent methods and comparison with Multisolid model in crude oil systems :

سال انتشار: 1388

محل انتشار: ششمین کنگره بین المللی مهندسی شیمی

تعداد صفحات: 6

چکیده:

This paper introduces a new implementation of the neural network and genetic programming neural network technology in petroleum engineering. An intelligent framework is developed for calculating the amount of wax precipitation in petroleum mixtures over a wide temperature range. Theoretical results and practical experience indicate that feed-forward network can approximate a wide class of function relationships very well. In this work, a conventional feed-forward multilayer Neural Network and Genetic Programming Neural Network (GPNN) approach have been proposed to predict the amount of wax precipitation. The introduced model can predict wax precipitation through neural network and genetic algorithmic techniques. The accuracy of the method is evaluated by predicting the amount of wax precipitation of various reservoir fluids not used in the development of the models. Furthermore, the performance of the model is compared with the performance of multi-solid model for wax precipitation prediction and experimental data. Results of this comparison show that the proposed method is superior, in both accuracy and generality, over the other models.

 

 

دانلود این فایل

 

کلمات کلیدی :