یک مدل شبکه عصبی بازگشتی برای حل برنامه ریزی خطی نیمه معین
Publish place: Caspian Journal of Mathematical Sciences، Vol: 4، Issue: 2
Publish Year: 1394
Type: Journal paper
Language: English
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JR_CJMS-4-2_006
Index date: 8 October 2019
یک مدل شبکه عصبی بازگشتی برای حل برنامه ریزی خطی نیمه معین abstract
In this paper we solve a wide rang of Semidefinite Programming (SDP) Problem by using Recurrent Neural Networks (RNNs).
SDP is an important numerical tool for analysis and synthesis in systems and control theory. First we reformulate the problem to a linear programming problem, second we reformulate it to a first order system of ordinary differential equations.
Then a recurrent neural network model is proposed to compute related primal and dual solutions simultaneously.Illustrative examples are included to demonstrate the validity and applicability of the technique.
یک مدل شبکه عصبی بازگشتی برای حل برنامه ریزی خطی نیمه معین Keywords:
یک مدل شبکه عصبی بازگشتی برای حل برنامه ریزی خطی نیمه معین authors
S. M. Mirhosseini Alizamini
Department of Mathematics, Payame Noor University, Tehran, Iran
A. Malek
Department of Applied Mathematics, faculty of Mathematical Sciences,Tarbiat Modares University, Tehrasn, Iran
Gh. Ahmadi
Department of Mathematics, Payame Noor University, Tehran, Iran