Adjoint method is widely used in aerodynamic design because only once solution of flow field required for it to obtain the gradients all variables. However, computational cost adjoint vector approximately equal that computation. In order accelerate and improve efficiency adjoint-based optimization, machine learning modeling presented. Deep neural network (DNN) employed construct mapping between...

Starting from second-order conditions for C scalar unconstrained optimization problems described in terms of the second-order Dini directional derivative, we pose the problem, whether similar conditions for C vector optimization problems can be derived. We define second-order Dini directional derivatives for vector functions and apply them to formulate such conditions as a Conjecture. The proof...