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Deep inference: A convolutional neural networks method for parameter recovery of the fractional dynamics | ||
International Journal of Nonlinear Analysis and Applications | ||
مقاله 16، دوره 12، شماره 1، مرداد 2021، صفحه 189-201 اصل مقاله (1.83 M) | ||
نوع مقاله: Research Paper | ||
شناسه دیجیتال (DOI): 10.22075/ijnaa.2021.4757 | ||
نویسندگان | ||
Nader Biranvand* 1؛ Amir Hossein Hadian-Rasanan2؛ Ali Khalili3؛ Jamal Amani Rad2 | ||
1Faculty of Sciences, Imam Ali University, Tehran, Iran | ||
2Department of Cognitive Modeling, Institute for Cognitive and Brain Sciences, Shahid Beheshti University, Tehran, Iran | ||
3Faculty of Engineering, Imam Ali University, Tehran Iran | ||
تاریخ دریافت: 21 اردیبهشت 1399، تاریخ بازنگری: 01 دی 1399، تاریخ پذیرش: 06 دی 1399 | ||
چکیده | ||
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. | ||
کلیدواژهها | ||
Convolutional neural network؛ Parameter estimation؛ Fractional Dynamics؛ Data driven discove | ||
مراجع | ||
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