A new algorithm helps topology optimizers skip unnecessary iterations, making optimization and design faster, more stable and ...

The strength of certain neural connections can predict how well someone can learn math, and mildly electrically stimulating these networks can boost learning, according to a study published in the ...

In this paper, a one-layer recurrent neural network is presented for solving pseudoconvex optimization problems subject to linear equality constraints. The global convergence of the neural network can ...

We describe a novel framework for the modeling and optimization of dynamic process networks based on network theory. Global optimization of nonlinear systems is investigated for dynamic flow problems.