In this paper, we study a gradient-based neural network method for solving strictly convex
quadratic programming (SCQP) problems. By converting the SCQP problem into a system of …

Shot peening is well-known process for mechanical properties integrity in metallic materials.
In present study influences of different shot peening treatments on the surface hardness of …

This paper proposes a neural network model for solving convex quadratic programming
(CQP) problems, whose equilibrium points coincide with Karush–Kuhn–Tucker (KKT) points …

Gras** force optimization (GFO) is a crucial step in multi-arm manipulation tasks, aiming to
suitably distribute the external force applied on the target to manipulators. The problem has …

This paper presents a gradient neural network model for solving convex nonlinear
programming (CNP) problems. The main idea is to convert the CNP problem into an …

The present scientific attempt is devoted to investigating the fuzzy nonconvex optimization
problems (NCOPs) utilizing the concepts of recurrent neural networks (RNNs). To the best of …

In this paper, we apply a gradient neural network model to efficiently solve the convex
second-order cone constrained variational inequality problem. According to a smoothing …

In this paper, we summarize several systematic ways of constructing smoothing functions
and illustrate eight smoothing functions accordingly. Then, based on these systematically …

This paper deals with a numerical technique for fractional optimal control problems (FOCPs)
based on a neural network scheme. The fractional derivative in these problems is in the …

In this paper, we consider a new neural network model to simply solve the convex second-
order cone constrained variational inequality problem. Based on a smoothing method, the …