کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
168264 | 1423462 | 2007 | 7 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Splicing System Based Genetic Algorithms for Developing RBF Networks Models*
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موضوعات مرتبط
مهندسی و علوم پایه
مهندسی شیمی
مهندسی شیمی (عمومی)
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
A splicing system based genetic algorithm is proposed to optimize dynamical radial basis function (RBF) neural network, which is used to extract valuable process information from input output data. The novel RBF network training technique includes the network structure into the set of function centers by compromising between the conflicting requirements of reducing prediction error and simultaneously decreasing model complexity. The effectiveness of the proposed method is illustrated through the development of dynamic models as a benchmark discrete example and a continuous stirred tank reactor by comparing with several different RBF network training methods.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Chinese Journal of Chemical Engineering - Volume 15, Issue 2, March 2007, Pages 240-246
Journal: Chinese Journal of Chemical Engineering - Volume 15, Issue 2, March 2007, Pages 240-246