کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4946378 1439283 2017 13 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Model turbine heat rate by fast learning network with tuning based on ameliorated krill herd algorithm
ترجمه فارسی عنوان
نرخ حرارت توربین مدل با استفاده از شبکه یادگیری سریع با تنظیم بر اساس الگوریتم گله کریل بهبود یافته است
کلمات کلیدی
الگوریتم گله کریل، شبکه آموزش سریع نرخ حرارت، توربین بخار،
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
چکیده انگلیسی
The krill herd (KH) is an innovative biologically-inspired algorithm. To improve the solution quality and to quicken the global convergence speed of KH, an ameliorated krill herd algorithm (A-KH) is proposed to solve the aforementioned problems and test it by classical benchmark functions, which is one of the major contributions of this paper. Compared with other several state-of-art optimization algorithms (biogeography-based optimization, particle swarm optimization, artificial bee colony and krill herd algorithm), A-KH shows better search performance. There is, furthermore, another contribution that the A-KH is adopted to adjust the parameters of the fast learning network (FLN) so as to build the turbine heat rate model of a 600MW supercritical steam and obtain a high-precision prediction model. Experimental results show that, compared with other several turbine heat rate models, the tuned FLN model by A-KH has better regression precision and generalization capability.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Knowledge-Based Systems - Volume 118, 15 February 2017, Pages 80-92
نویسندگان
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