کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6864393 | 1439541 | 2018 | 11 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
A modified Elman neural network with a new learning rate scheme
ترجمه فارسی عنوان
یک شبکه عصبی المان با یک برنامه یادگیری جدید
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کلمات کلیدی
المان شبکه عصبی، نرخ یادگیری، اثبات همگرایی،
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
چکیده انگلیسی
Elman neural network (ENN) is one of recurrent neural networks (RNNs). Comparing to traditional neural networks, ENN has additional inputs from the hidden layer, which forms a new layer-the context layer. So the standard back-propagation (BP) algorithm used in ENN is called Elman back-propagation algorithm (EBP). ENN can be applied to solve prediction problems of discrete time sequence. However, the EBP algorithm suffers from low convergence speed and poor generalization performance. To solve this problem, a new learning rate scheme is proposed, the convergence of new proposed scheme is proved. Furthermore, the contrast experiment is utilized to demonstrate the effectiveness of the proposed scheme from the aspects of convergence speed and consumption time with some popular schemes such as the original ENN, and PSO-ENN which uses PSO algorithm to search the best structure of ENN. The experience shows that the modified method proposed in this paper works best.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Neurocomputing - Volume 286, 19 April 2018, Pages 11-18
Journal: Neurocomputing - Volume 286, 19 April 2018, Pages 11-18
نویسندگان
Guanghua Ren, Yuting Cao, Shiping Wen, Tingwen Huang, Zhigang Zeng,