MATLAB Simulink Modeling and Simulation of Recurrent Neural Network for Solving Linear Programming Problems
نویسنده
چکیده
In this paper, a recurrent neural network for solving linear programming problems is presented that is simpler, intuitive and fast converging. To achieve optimality in accuracy and also in computational effort, an algorithm is presented. We investigate in this paper the MATLAB Simulink modeling and simulative verification of such a recurrent neural network. Modeling and simulative results substantiate the theoretical analysis and efficacy of the recurrent neural network for solving the linear programming problem. A detailed example has been presented to demonstrate the performance of the recurrent neural network.
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