کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
13428815 | 1842298 | 2020 | 7 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Comparing of deep neural networks and extreme learning machines based on growing and pruning approach
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
Recently, the studies based on Deep Neural Networks and Extreme Learning Machines have become prominent. The models of parameters designed in these studies have been chosen randomly and the models have been designed in this direction. The main focus of this study is to determine the ideal parameters i.e. optimum hidden layer number, optimum hidden neuron number and activation function for Deep Neural Networks and Extreme Learning Machines architectures based on growing and pruning approach and to compare the performances of the models designed. The performances of the models are evaluated on two datasets; Parkinson and Self-Care Activities Dataset. Multi experiments have verified that the Deep Neural Networks architectures present a good prediction performance and this architecture outperforms the Extreme Learning Machines.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Expert Systems with Applications - Volume 140, February 2020, 112875
Journal: Expert Systems with Applications - Volume 140, February 2020, 112875
نویسندگان
Kemal Akyol,