Conjugate gradient method is a numerical method that can find the minima of the function in the hyper-dimensional space, and conjugate gradient method includes linear conjugate method and non-linear ...

Conjugate gradient methods form a class of iterative algorithms that are highly effective for solving large‐scale unconstrained optimisation problems. They achieve efficiency by constructing search ...

The nonlinear conjugate gradient method is a very useful technique for solving large scale minimization problems and has wide applications in many fields. In this paper, we present a new algorithm of ...

Abstract: For the conjugate gradient method to solve the unconstrained optimization problem, given a new interval method to obtain the direction parameters, and a new conjugate gradient algorithm is ...

Abstract: This paper extends the conjugate gradient minimization method of Fletcher and Reeves to optimal control problems. The technique is directly applicable only to unconstrained problems; if ...

NCG-Optimizer is a set of optimizer about nonlinear conjugate gradient in PyTorch. Inspired by @jettify and @kozistr. The Linear Conjugate Gradient(LCG) method is only applicable to linear equation ...

This paper proposes a bridge moving load identification method based on the Fractional Conjugate Gradient (FCG) method to address the low identification accuracy of traditional conjugate gradient ...

ABSTRACT: In conjugate gradient method, it is well known that the recursively computed residual differs from true one as the iteration proceeds in finite arithmetic. Some work have been devoted to ...

ABSTRACT: In this paper, an efficient computational algorithm is proposed to solve the nonlinear optimal control problem. In our approach, the linear quadratic optimal control model, which is adding ...