کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
5146195 | 1497348 | 2017 | 10 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Flowing bottomhole pressure prediction for gas wells based on support vector machine and random samples selection
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کلمات کلیدی
ANNSVRRBFMSETRSVESMATLAB program - برنامه MATLABSupport vector regression - رگرسیون بردار پشتیبانیartificial neural networks - شبکه های عصبی مصنوعیRadial basis function - عملکرد پایه شعاعیSupport vector machine - ماشین بردار پشتیبانیSVM - ماشین بردار پشتیبانیMean Square Error - میانگین مربع خطاGas wells - چاه های گاز
موضوعات مرتبط
مهندسی و علوم پایه
شیمی
الکتروشیمی
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
Dynamic analysis and optimum production strategies of gas wells demand accurate prediction of flowing bottomhole pressure (FBHP). Due to the existence of many uncertain relations between the changeable influence factors and the limitations of existing methods, no single model was found to be applicable over all ranges of variables with suitable accuracy. In this paper, a FBHP prediction method based on support vector machine (SVM) and random samples selection way, named the FBHP-SVM method, was investigated, and a support vector regression model with É-insensitive loss function (É-SVR) based on radial basis function (RBF) was used to predict the FBHP. Compared with the true values, the average absolute and relative prediction errors were 0.20Â MPa and 2.62%, respectively. It is worthy to note that a reliable prediction of FBHB can be made when the true value of verification data is in the true values range of training samples.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: International Journal of Hydrogen Energy - Volume 42, Issue 29, 20 July 2017, Pages 18333-18342
Journal: International Journal of Hydrogen Energy - Volume 42, Issue 29, 20 July 2017, Pages 18333-18342
نویسندگان
Wei Chen, Qinfeng Di, Feng Ye, Jingnan Zhang, Wenchang Wang,