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We develop a projection recurrent neural network (RNN) to obtain the solution of the shortest path problem (SPP). Our focus on the paper is to give a compact single-layer structure RNN model to solve the SPP. To present the RNN model, we utilise a mixed linear complementarity problem (MLCP). Moreover, the developed RNN is proved to be globally stable. Finally, some numerical simulations are stated to show the performance of the presented approach. We compare the results with some other methods. [ABSTRACT FROM AUTHOR]

In this scientific research, a new technique to solve a linear quadratic optimal control problem with fuzzy variables is proposed. The problem by an efficient transformation reduces to a crisp problem, and the solution is obtained from the direct method. In fact, we use the approximation method with artificial neural network, and to obtain the solution, the perceptron neural network (PNN) is given. Finally, two numerical examples are presented to show the performance of the technique. [ABSTRACT FROM AUTHOR]