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Computationally Efficient Data-Driven Topology Design Independent from High-Infoentropy Initial Dataset
Topology optimization (TO) has been widely adopted in engineering design; however, it is prone to being trapped in local optima, particularly in strongly nonlinear problems. Sensitivity-free data-driven topology design (DDTD) offers a promising alternative. Nevertheless, existing DDTD-based methods
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