کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
410390 | 679140 | 2010 | 8 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Constructive training of recurrent neural networks using hybrid optimization
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: Constructive training of recurrent neural networks using hybrid optimization Constructive training of recurrent neural networks using hybrid optimization](/preview/png/410390.png)
چکیده انگلیسی
Training of recurrent neural networks (RNNs) is known to be a very difficult task. This work proposes a novel constructive method for simultaneous structure and parameter training of Elman-type RNNs using a combination of particle swarm optimization (PSO) and covariance matrix adaptation based evolutionary strategy (CMA-ES). The proposed method allows the imposition of certain stability conditions, which can be maintained throughout the constructive process. The examples reported show a monotonic decrease in training error throughout the constructive process and also demonstrate the efficiency of the proposed method for structure and parameter training of RNNs.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Neurocomputing - Volume 73, Issues 13–15, August 2010, Pages 2624–2631
Journal: Neurocomputing - Volume 73, Issues 13–15, August 2010, Pages 2624–2631
نویسندگان
Niranjan Subrahmanya, Yung C. Shin,