Title : ( Projection Recurrent Neural Network Model: A New Strategy to Solve Weapon-Target Assignment Problem )
Authors: Alireza Shojaeifard , Ali Nakhaei Amroudi , Amin Mansoori , Majid Erfanian ,
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Abstract
In the present research, we are going to obtain the solution of the Weapon-Target Assignment (WTA) problem. According to our search in the scientific reported papers, this is the first scientific attempt for resolving of WTA problem by projection recurrent neural network (RNN) models. Here, by reformulating the original problem to an unconstrained problem a projection RNN model as a high-performance tool to provide the solution of the problem is proposed. In continuous, the global exponential stability of the system was proved in this research. In the final step, some numerical examples are presented to depict the performance and the feasibility of the method. Reported results were compared with some other published papers
Keywords
, Weapon, target assignment problem Nonlinear optimization problem Projection recurrent neural network Global exponential stability Projection function
@article{paperid:1075955,
author = {علیرضا شجاعی فرد and Ali Nakhaei Amroudi and Mansoori, Amin and مجید عرفانیان},
title = {Projection Recurrent Neural Network Model: A New Strategy to Solve Weapon-Target Assignment Problem},
journal = {Neural Processing Letters},
year = {2019},
volume = {50},
number = {3},
month = {December},
issn = {1370-4621},
pages = {3045--3057},
numpages = {12},
keywords = {Weapon-target assignment problem Nonlinear optimization problem Projection recurrent neural network Global exponential stability Projection function},
}
%0 Journal Article
%T Projection Recurrent Neural Network Model: A New Strategy to Solve Weapon-Target Assignment Problem
%A علیرضا شجاعی فرد
%A Ali Nakhaei Amroudi
%A Mansoori, Amin
%A مجید عرفانیان
%J Neural Processing Letters
%@ 1370-4621
%D 2019
