کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
8072383 | 1521406 | 2018 | 14 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Investigation of Support Vector Machine and Back Propagation Artificial Neural Network for performance prediction of the organic Rankine cycle system
ترجمه فارسی عنوان
بررسی وکتور ماشین بردار پشتیبانی و گسترش شبکه عصبی مصنوعی برای پیش بینی عملکرد سیستم چرخه ارگانیک
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موضوعات مرتبط
مهندسی و علوم پایه
مهندسی انرژی
انرژی (عمومی)
چکیده انگلیسی
Low temperature power generation system based on organic Rankine cycle (ORC) has been a popular candidate for low grade heat utilization and recovery. To find a way to predict the performance of the ORC system, the exploration and analyses of the Support Vector Machine (SVM) and Back Propagation Artificial Neural Network (BP-ANN) were carried out. For comparison, both Gauss Radial Basis kernel function (SVM-RBF) and linear function (SVM-LF) have been employed in SVM. Additionally, for the sake of comprehensiveness, two division methods for data set called “random division method” and “blocked division method” were studied. Finally, SVM-LF and BP-ANN demonstrated better stability and higher accuracy for both two division methods and for different testing sets while SVM-RBF showed good results for random division method and disappointing results for blocked division method.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Energy - Volume 144, 1 February 2018, Pages 851-864
Journal: Energy - Volume 144, 1 February 2018, Pages 851-864
نویسندگان
Shengming Dong, Yufeng Zhang, Zhonglu He, Na Deng, Xiaohui Yu, Sheng Yao,