کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
381684 | 1437516 | 2006 | 7 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
A sliding window solution for the on-line implementation of the Levenberg–Marquardt algorithm
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
The Levenberg–Marquardt algorithm is considered as the most effective one for training artificial neural networks but its computational complexity and the difficulty to compute the trust region have made it very difficult to develop a true iterative version to use in on-line training. The algorithm is frequently used for off-line training in batch versions although some attempts have been made to implement iterative versions. To overcome the difficulties in implementing the iterative version, a batch-sliding window with Early Stopping, which uses a hybrid Direct/Specialized evaluation procedure, is proposed and tested with a real system.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Engineering Applications of Artificial Intelligence - Volume 19, Issue 1, February 2006, Pages 1–7
Journal: Engineering Applications of Artificial Intelligence - Volume 19, Issue 1, February 2006, Pages 1–7
نویسندگان
Fernando Morgado Dias, Ana Antunes, José Vieira, Alexandre Mota,