کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
8147350 | 1524144 | 2017 | 8 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Clustering algorithms application to forming a representative sample in the training of a multilayer perceptron
ترجمه فارسی عنوان
استفاده از الگوریتم های خوشه بندی برای تشکیل یک نمونه نمایشی در آموزش پریترونون چند لایه
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کلمات کلیدی
شبکه عصبی، الگوریتم خوشه بندی، نمونه، پراپرترون چند لایه
موضوعات مرتبط
مهندسی و علوم پایه
فیزیک و نجوم
فیزیک اتمی و مولکولی و اپتیک
چکیده انگلیسی
In this paper, we have considered the problem of effectively forming the representative sample for training a neural network of the multilayer perceptron (MLP) type. An approach based on the use of clustering that allowed to increase the entropy of the training set was put forward. Various clustering algorithms were examined in order to form the representative sample. The algorithm-based clustering of factor spaces of various dimensions was carried out, and a representative sample was formed. To verify our approach we synthesized the MLP neural network and trained it. The training technique was performed with the sets formed both with and without clustering. A comparative analysis of the effectiveness of clustering algorithms was carried out in relation to the problem of representative sample formation.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: St. Petersburg Polytechnical University Journal: Physics and Mathematics - Volume 3, Issue 2, June 2017, Pages 127-134
Journal: St. Petersburg Polytechnical University Journal: Physics and Mathematics - Volume 3, Issue 2, June 2017, Pages 127-134
نویسندگان
Aleksey A. Pastukhov, Aleksander A. Prokofiev,