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Abstract: This paper introduces neuroevolution for solving differential equations. The solution is obtained through optimizing a deep neural network whose loss function is defined by the residual ...
Abstract: In this article, we propose an efficient Takagi–Sugeno fuzzy zeroing neural network (TS-FZNN) activated by a new activation function for solving the time-varying Sylvester equation. The self ...