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Deep inference: A convolutional neural networks method for parameter recovery of the fractional dynamics

عنوان مقاله: Deep inference: A convolutional neural networks method for parameter recovery of the fractional dynamics
شناسه ملی مقاله: JR_IJNAA-12-1_016
منتشر شده در در سال 1400
مشخصات نویسندگان مقاله:

- - - Faculty of Sciences, Imam Ali University, Tehran, Iran
- - - Department of Cognitive Modeling, Institute for Cognitive and Brain Sciences, Shahid Beheshti University, Tehran, Iran
- - - Faculty of Engineering, Imam Ali University, Tehran Iran
- - - Department of Cognitive Modeling, Institute for Cognitive and Brain Sciences, Shahid Beheshti University, Tehran, Iran

خلاصه مقاله:
Parameter recovery of dynamical systems has attracted much attention in recent years. The proposed methods for this purpose can not be used in real-time applications. Besides, little works have been done on the parameter recovery of the fractional dynamics. Therefore, in this paper, a convolutional neural network is proposed for parameter recovery of the fractional dynamics. The presented network can also estimate the uncertainty of the parameter estimation and has perfect robustness for real-time applications.

کلمات کلیدی:
Convolutional Neural Network, Parameter estimation, Fractional Dynamics, Data driven discove

صفحه اختصاصی مقاله و دریافت فایل کامل: https://civilica.com/doc/1561296/